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JoeNoss1998/FineTunedModel | JoeNoss1998 | "2024-09-18T23:10:16Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"trl",
"sft",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"region:us"
] | text-generation | "2024-09-18T23:05:33Z" | ---
library_name: transformers
tags:
- trl
- sft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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[More Information Needed]
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utahnlp/naturalquestionsShort_facebook_opt-13b_seed-1 | utahnlp | "2024-09-18T23:15:43Z" | 0 | 0 | null | [
"safetensors",
"opt",
"region:us"
] | null | "2024-09-18T23:05:45Z" | Entry not found |
mishakkk/starcoder2-instruct-code-3 | mishakkk | "2024-09-18T23:05:58Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | "2024-09-18T23:05:48Z" | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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[More Information Needed]
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John6666/2dn-pony-v10play-sdxl | John6666 | "2024-09-18T23:10:14Z" | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"text-to-image",
"stable-diffusion",
"stable-diffusion-xl",
"anime",
"realistic",
"semirealistic",
"2.5D",
"pony",
"en",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | text-to-image | "2024-09-18T23:05:53Z" | ---
license: other
license_name: faipl-1.0-sd
license_link: https://freedevproject.org/faipl-1.0-sd/
language:
- en
library_name: diffusers
pipeline_tag: text-to-image
tags:
- text-to-image
- stable-diffusion
- stable-diffusion-xl
- anime
- realistic
- semirealistic
- 2.5D
- pony
---
Original model is [here](https://civitai.com/models/520661?modelVersionId=801921).
This model created by [advokat](https://civitai.com/user/advokat).
|
SALUTEASD/Qwen-Qwen1.5-0.5B-1726700791 | SALUTEASD | "2024-09-18T23:06:37Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-18T23:06:30Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
# Model Card for Model ID
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## Model Details
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[More Information Needed]
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phdatdt/madlad400-3b-mt-finetuned-en-to-fr | phdatdt | "2024-09-18T23:06:38Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:06:38Z" | Entry not found |
tronsdds/google-gemma-2b-1726700828 | tronsdds | "2024-09-18T23:07:42Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-18T23:07:08Z" | ---
base_model: google/gemma-2b
library_name: peft
---
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novalalthoff/wav2vec2-large-xlsr-53-id-google-fleurs-50 | novalalthoff | "2024-09-18T23:09:19Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | "2024-09-18T23:07:29Z" | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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[More Information Needed]
## Training Details
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[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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KingArf/9822v2 | KingArf | "2024-09-18T23:07:40Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:07:40Z" | Entry not found |
dogssss/Qwen-Qwen1.5-1.8B-1726700964 | dogssss | "2024-09-18T23:09:28Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-18T23:09:24Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
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SuperMari/Torrie | SuperMari | "2024-09-18T23:15:25Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:09:37Z" | Entry not found |
SALUTEASD/Qwen-Qwen1.5-1.8B-1726700989 | SALUTEASD | "2024-09-18T23:10:01Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-18T23:09:48Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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tronsdds/google-gemma-7b-1726701050 | tronsdds | "2024-09-18T23:11:38Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-7b",
"base_model:adapter:google/gemma-7b",
"region:us"
] | null | "2024-09-18T23:10:50Z" | ---
base_model: google/gemma-7b
library_name: peft
---
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huazi123/google-gemma-2b-1726701070 | huazi123 | "2024-09-18T23:11:15Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-18T23:11:08Z" | ---
base_model: google/gemma-2b
library_name: peft
---
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rana-shahroz/mistral-7b-lora-r8-math-epochs3-adapter | rana-shahroz | "2024-09-18T23:11:21Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | "2024-09-18T23:11:16Z" | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
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jag2023/Complete_final_phi-3_bug_report_generator | jag2023 | "2024-09-18T23:11:29Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | "2024-09-18T23:11:23Z" | ---
base_model: unsloth/phi-3.5-mini-instruct-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
---
# Uploaded model
- **Developed by:** jag2023
- **License:** apache-2.0
- **Finetuned from model :** unsloth/phi-3.5-mini-instruct-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
noblebarkrr/all_models_for_mel_band_roformer | noblebarkrr | "2024-09-18T23:34:21Z" | 0 | 0 | null | [
"license:gpl-3.0",
"region:us"
] | null | "2024-09-18T23:11:51Z" | ---
license: gpl-3.0
---
---
credits:
aufr33,
anyuew,
viperx,
Sucial,
Kimberly Jensen |
Krabat/Qwen-Qwen1.5-0.5B-1726701126 | Krabat | "2024-09-18T23:12:09Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-18T23:12:06Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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Rory618/ddpm-butterflies-128 | Rory618 | "2024-09-18T23:12:10Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:12:10Z" | Entry not found |
tronsdds/Qwen-Qwen1.5-1.8B-1726701188 | tronsdds | "2024-09-18T23:13:20Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-18T23:13:08Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
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drnko/receipt_model_aug24 | drnko | "2024-09-18T23:13:36Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:13:36Z" | Entry not found |
jerseyjerry/Qwen-Qwen2-1.5B-1726701222 | jerseyjerry | "2024-09-18T23:13:47Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen2-1.5B",
"base_model:adapter:Qwen/Qwen2-1.5B",
"region:us"
] | null | "2024-09-18T23:13:42Z" | ---
base_model: Qwen/Qwen2-1.5B
library_name: peft
---
# Model Card for Model ID
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dogssss/Qwen-Qwen1.5-0.5B-1726701236 | dogssss | "2024-09-18T23:14:01Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-18T23:13:57Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
# Model Card for Model ID
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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### Framework versions
- PEFT 0.12.0 |
saxon/multillava-next-vicuna7b-siglip-finetune1.5-lfr1e-3-105000 | saxon | "2024-09-18T23:23:20Z" | 0 | 0 | null | [
"safetensors",
"llama",
"region:us"
] | null | "2024-09-18T23:14:01Z" | Entry not found |
superkaiba1/wiki-art_denoising_frequency_seeds_low6seed23456 | superkaiba1 | "2024-09-18T23:14:24Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:24Z" | Entry not found |
superkaiba1/wiki-art_denoising_frequency_seeds_low8seed23456 | superkaiba1 | "2024-09-18T23:14:24Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:24Z" | Entry not found |
superkaiba1/wiki-art_denoising_frequency_seeds_low5seed23456 | superkaiba1 | "2024-09-18T23:14:24Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:24Z" | Entry not found |
superkaiba1/wiki-art_denoising_frequency_seeds_low2seed23456 | superkaiba1 | "2024-09-18T23:14:24Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:24Z" | Entry not found |
superkaiba1/wiki-art_denoising_frequency_seeds_low4seed23456 | superkaiba1 | "2024-09-18T23:14:24Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:24Z" | Entry not found |
superkaiba1/wiki-art_denoising_frequency_seeds_low3seed23456 | superkaiba1 | "2024-09-18T23:14:24Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:24Z" | Entry not found |
superkaiba1/wiki-art_denoising_frequency_seeds_low7seed23456 | superkaiba1 | "2024-09-18T23:14:24Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:24Z" | Entry not found |
huazi123/Qwen-Qwen1.5-0.5B-1726701278 | huazi123 | "2024-09-18T23:14:41Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-18T23:14:36Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
# Model Card for Model ID
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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### Framework versions
- PEFT 0.12.0 |
Comasa/clonar_voz | Comasa | "2024-09-19T22:45:48Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:43Z" | Entry not found |
superkaiba1/domainnet-quickdraw_denoising_frequency_seeds_low6seed23456 | superkaiba1 | "2024-09-18T23:14:45Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:45Z" | Entry not found |
superkaiba1/domainnet-quickdraw_denoising_frequency_seeds_low4seed23456 | superkaiba1 | "2024-09-18T23:14:45Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:45Z" | Entry not found |
superkaiba1/domainnet-quickdraw_denoising_frequency_seeds_low5seed23456 | superkaiba1 | "2024-09-18T23:14:46Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:45Z" | Entry not found |
superkaiba1/domainnet-quickdraw_denoising_frequency_seeds_low3seed23456 | superkaiba1 | "2024-09-18T23:14:46Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:46Z" | Entry not found |
superkaiba1/domainnet-quickdraw_denoising_frequency_seeds_low7seed23456 | superkaiba1 | "2024-09-18T23:14:46Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:46Z" | Entry not found |
superkaiba1/domainnet-quickdraw_denoising_frequency_seeds_low2seed23456 | superkaiba1 | "2024-09-18T23:14:46Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:46Z" | Entry not found |
superkaiba1/domainnet-quickdraw_denoising_frequency_seeds_low8seed23456 | superkaiba1 | "2024-09-18T23:14:46Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:46Z" | Entry not found |
superkaiba1/CelebA_denoising_frequency_seeds_low4seed23456 | superkaiba1 | "2024-09-18T23:14:47Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:47Z" | Entry not found |
superkaiba1/CelebA_denoising_frequency_seeds_low7seed23456 | superkaiba1 | "2024-09-18T23:14:47Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:47Z" | Entry not found |
superkaiba1/CelebA_denoising_frequency_seeds_low8seed23456 | superkaiba1 | "2024-09-18T23:14:47Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:47Z" | Entry not found |
superkaiba1/CelebA_denoising_frequency_seeds_low5seed23456 | superkaiba1 | "2024-09-18T23:14:47Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:47Z" | Entry not found |
superkaiba1/CelebA_denoising_frequency_seeds_low3seed23456 | superkaiba1 | "2024-09-18T23:14:47Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:47Z" | Entry not found |
superkaiba1/CelebA_denoising_frequency_seeds_low6seed23456 | superkaiba1 | "2024-09-18T23:14:47Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:14:47Z" | Entry not found |
tronsdds/google-gemma-2b-1726701297 | tronsdds | "2024-09-18T23:15:32Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-18T23:14:58Z" | ---
base_model: google/gemma-2b
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## Technical Specifications [optional]
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## Model Card Contact
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### Framework versions
- PEFT 0.12.0 |
utahnlp/naturalquestionsShort_gpt2_seed-1 | utahnlp | "2024-09-18T23:16:11Z" | 0 | 0 | null | [
"safetensors",
"gpt2",
"region:us"
] | null | "2024-09-18T23:15:48Z" | Entry not found |
SALUTEASD/Qwen-Qwen1.5-0.5B-1726701354 | SALUTEASD | "2024-09-18T23:15:58Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-18T23:15:53Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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## Environmental Impact
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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## Model Card Contact
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### Framework versions
- PEFT 0.12.0 |
utahnlp/naturalquestionsShort_gpt2_seed-2 | utahnlp | "2024-09-18T23:16:34Z" | 0 | 0 | null | [
"safetensors",
"gpt2",
"region:us"
] | null | "2024-09-18T23:16:15Z" | Entry not found |
utahnlp/naturalquestionsShort_gpt2_seed-3 | utahnlp | "2024-09-18T23:17:00Z" | 0 | 0 | null | [
"safetensors",
"gpt2",
"region:us"
] | null | "2024-09-18T23:16:38Z" | Entry not found |
ShashwatDifff/Calcium | ShashwatDifff | "2024-09-18T23:18:22Z" | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | "2024-09-18T23:17:06Z" | Entry not found |
utahnlp/naturalquestionsShort_gpt2-medium_seed-1 | utahnlp | "2024-09-18T23:17:59Z" | 0 | 0 | null | [
"safetensors",
"gpt2",
"region:us"
] | null | "2024-09-18T23:17:07Z" | Entry not found |
utahnlp/naturalquestionsShort_gpt2-medium_seed-2 | utahnlp | "2024-09-18T23:18:58Z" | 0 | 0 | null | [
"safetensors",
"gpt2",
"region:us"
] | null | "2024-09-18T23:18:06Z" | Entry not found |
Sivarishi/search | Sivarishi | "2024-09-18T23:18:25Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:18:25Z" | Entry not found |
tronsdds/google-gemma-7b-1726701521 | tronsdds | "2024-09-18T23:20:28Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-7b",
"base_model:adapter:google/gemma-7b",
"region:us"
] | null | "2024-09-18T23:18:41Z" | ---
base_model: google/gemma-7b
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- PEFT 0.12.0 |
dogssss/Qwen-Qwen1.5-1.8B-1726701544 | dogssss | "2024-09-18T23:19:08Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-18T23:19:04Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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[More Information Needed]
## Training Details
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### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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## Technical Specifications [optional]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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### Framework versions
- PEFT 0.12.0 |
utahnlp/naturalquestionsShort_gpt2-medium_seed-3 | utahnlp | "2024-09-18T23:19:49Z" | 0 | 0 | null | [
"safetensors",
"gpt2",
"region:us"
] | null | "2024-09-18T23:19:05Z" | Entry not found |
SALUTEASD/Qwen-Qwen1.5-1.8B-1726701551 | SALUTEASD | "2024-09-18T23:19:16Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-18T23:19:10Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
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[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
### Framework versions
- PEFT 0.12.0 |
John6666/iris-xl-10-sdxl | John6666 | "2024-09-18T23:26:43Z" | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"text-to-image",
"stable-diffusion",
"stable-diffusion-xl",
"anime",
"trained",
"novel ai",
"nai",
"anatomy",
"poses",
"artists",
"characters",
"en",
"license:creativeml-openrail-m",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | text-to-image | "2024-09-18T23:19:10Z" | ---
license: creativeml-openrail-m
language:
- en
library_name: diffusers
pipeline_tag: text-to-image
tags:
- text-to-image
- stable-diffusion
- stable-diffusion-xl
- anime
- trained
- novel ai
- nai
- anatomy
- poses
- artists
- characters
---
Original model is [here](https://civitai.com/models/758322/iris-xl?modelVersionId=847931).
This model created by [LyloGummy](https://civitai.com/user/LyloGummy). |
mlx-community/Qwen2.5-Math-1.5B-Instruct-8bit | mlx-community | "2024-09-18T23:20:22Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"mlx",
"conversational",
"en",
"base_model:Qwen/Qwen2.5-Math-1.5B",
"base_model:finetune:Qwen/Qwen2.5-Math-1.5B",
"license:apache-2.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | "2024-09-18T23:20:00Z" | ---
base_model: Qwen/Qwen2.5-Math-1.5B
language:
- en
library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen2.5-Math-1.5B-Instruct/blob/main/LICENSE
pipeline_tag: text-generation
tags:
- chat
- mlx
---
# mlx-community/Qwen2.5-Math-1.5B-Instruct-8bit
The Model [mlx-community/Qwen2.5-Math-1.5B-Instruct-8bit](https://huggingface.co/mlx-community/Qwen2.5-Math-1.5B-Instruct-8bit) was converted to MLX format from [Qwen/Qwen2.5-Math-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Math-1.5B-Instruct) using mlx-lm version **0.18.1**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Qwen2.5-Math-1.5B-Instruct-8bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)
```
|
utahnlp/naturalquestionsShort_gpt2-large_seed-1 | utahnlp | "2024-09-18T23:22:01Z" | 0 | 0 | null | [
"safetensors",
"gpt2",
"region:us"
] | null | "2024-09-18T23:20:02Z" | Entry not found |
kyle-enginable/vinsketch-1 | kyle-enginable | "2024-09-18T23:20:41Z" | 0 | 0 | diffusers | [
"diffusers",
"text-to-image",
"flux",
"lora",
"template:sd-lora",
"fluxgym",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | "2024-09-18T23:20:40Z" | ---
tags:
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
- fluxgym
widget:
- output:
url: sample/vinsketch-1_001250_00_20240918212238.png
text: in the style of V1NSK3TCH
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: in the style of V1NSK3TCH
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
---
# vinsketch-1
A Flux LoRA trained on a local computer with [Fluxgym](https://github.com/cocktailpeanut/fluxgym)
<Gallery />
## Trigger words
You should use `in the style of V1NSK3TCH` to trigger the image generation.
## Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, Forge, etc.
Weights for this model are available in Safetensors format.
|
huazi123/Qwen-Qwen1.5-1.8B-1726701690 | huazi123 | "2024-09-18T23:21:33Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-18T23:21:28Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
### Framework versions
- PEFT 0.12.0 |
tronsdds/Qwen-Qwen1.5-1.8B-1726701713 | tronsdds | "2024-09-18T23:22:05Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-18T23:21:53Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
### Framework versions
- PEFT 0.12.0 |
utahnlp/naturalquestionsShort_gpt2-large_seed-2 | utahnlp | "2024-09-18T23:24:11Z" | 0 | 0 | null | [
"safetensors",
"gpt2",
"region:us"
] | null | "2024-09-18T23:22:14Z" | Entry not found |
iliyararupzhanov/med-drugs-extraction | iliyararupzhanov | "2024-09-19T11:27:42Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"question-answering",
"generated_from_trainer",
"base_model:DeepPavlov/rubert-base-cased",
"base_model:finetune:DeepPavlov/rubert-base-cased",
"endpoints_compatible",
"region:us"
] | question-answering | "2024-09-18T23:22:32Z" | ---
library_name: transformers
base_model: DeepPavlov/rubert-base-cased
tags:
- generated_from_trainer
model-index:
- name: med-drugs-extraction
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# med-drugs-extraction
This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.0a0+81ea7a4
- Datasets 3.0.0
- Tokenizers 0.19.1
|
tronsdds/google-gemma-2b-1726701816 | tronsdds | "2024-09-18T23:23:37Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:23:37Z" | Entry not found |
dogssss/Qwen-Qwen1.5-0.5B-1726701818 | dogssss | "2024-09-18T23:23:43Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-18T23:23:38Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
### Framework versions
- PEFT 0.12.0 |
utahnlp/naturalquestionsShort_gpt2-large_seed-3 | utahnlp | "2024-09-18T23:26:19Z" | 0 | 0 | null | [
"safetensors",
"gpt2",
"region:us"
] | null | "2024-09-18T23:24:24Z" | Entry not found |
Downtown-Case/Qwen_Qwen2.5-32B-Base-exl2-3.62bpw | Downtown-Case | "2024-09-19T19:47:29Z" | 0 | 0 | null | [
"safetensors",
"qwen2",
"text-generation",
"conversational",
"en",
"base_model:Qwen/Qwen2.5-32B",
"base_model:quantized:Qwen/Qwen2.5-32B",
"license:apache-2.0",
"exl2",
"region:us"
] | text-generation | "2024-09-18T23:24:44Z" | ---
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen2.5-32B/blob/main/LICENSE
language:
- en
pipeline_tag: text-generation
base_model:
- Qwen/Qwen2.5-32B
---
# Quantization
3.62bpw quantization using default settings, for (probably?) full context on a 24G GPU.
This is the base model, not instruct! Base models tend to be better for raw completion, especially at long context.
# Qwen2.5-32B
## Introduction
Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:
- Significantly **more knowledge** and has greatly improved capabilities in **coding** and **mathematics**, thanks to our specialized expert models in these domains.
- Significant improvements in **instruction following**, **generating long texts** (over 8K tokens), **understanding structured data** (e.g, tables), and **generating structured outputs** especially JSON. **More resilient to the diversity of system prompts**, enhancing role-play implementation and condition-setting for chatbots.
- **Long-context Support** up to 128K tokens and can generate up to 8K tokens.
- **Multilingual support** for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.
**This repo contains the base 32B Qwen2.5 model**, which has the following features:
- Type: Causal Language Models
- Training Stage: Pretraining
- Architecture: transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias
- Number of Parameters: 32.5B
- Number of Paramaters (Non-Embedding): 31.0B
- Number of Layers: 64
- Number of Attention Heads (GQA): 40 for Q and 8 for KV
- Context Length: 131,072 tokens
**We do not recommend using base language models for conversations.** Instead, you can apply post-training, e.g., SFT, RLHF, continued pretraining, etc., on this model.
For more details, please refer to our [blog](https://qwenlm.github.io/blog/qwen2.5/), [GitHub](https://github.com/QwenLM/Qwen2.5), and [Documentation](https://qwen.readthedocs.io/en/latest/).
## Requirements
The code of Qwen2.5 has been in the latest Hugging face `transformers` and we advise you to use the latest version of `transformers`.
With `transformers<4.37.0`, you will encounter the following error:
```
KeyError: 'qwen2'
```
## Evaluation & Performance
Detailed evaluation results are reported in this [📑 blog](https://qwenlm.github.io/blog/qwen2.5/).
For requirements on GPU memory and the respective throughput, see results [here](https://qwen.readthedocs.io/en/latest/benchmark/speed_benchmark.html).
## Citation
If you find our work helpful, feel free to give us a cite.
```
@misc{qwen2.5,
title = {Qwen2.5: A Party of Foundation Models},
url = {https://qwenlm.github.io/blog/qwen2.5/},
author = {Qwen Team},
month = {September},
year = {2024}
}
@article{qwen2,
title={Qwen2 Technical Report},
author={An Yang and Baosong Yang and Binyuan Hui and Bo Zheng and Bowen Yu and Chang Zhou and Chengpeng Li and Chengyuan Li and Dayiheng Liu and Fei Huang and Guanting Dong and Haoran Wei and Huan Lin and Jialong Tang and Jialin Wang and Jian Yang and Jianhong Tu and Jianwei Zhang and Jianxin Ma and Jin Xu and Jingren Zhou and Jinze Bai and Jinzheng He and Junyang Lin and Kai Dang and Keming Lu and Keqin Chen and Kexin Yang and Mei Li and Mingfeng Xue and Na Ni and Pei Zhang and Peng Wang and Ru Peng and Rui Men and Ruize Gao and Runji Lin and Shijie Wang and Shuai Bai and Sinan Tan and Tianhang Zhu and Tianhao Li and Tianyu Liu and Wenbin Ge and Xiaodong Deng and Xiaohuan Zhou and Xingzhang Ren and Xinyu Zhang and Xipin Wei and Xuancheng Ren and Yang Fan and Yang Yao and Yichang Zhang and Yu Wan and Yunfei Chu and Yuqiong Liu and Zeyu Cui and Zhenru Zhang and Zhihao Fan},
journal={arXiv preprint arXiv:2407.10671},
year={2024}
}
``` |
Krabat/Qwen-Qwen1.5-1.8B-1726701895 | Krabat | "2024-09-18T23:24:58Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-18T23:24:56Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
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- **Developed by:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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### Model Sources [optional]
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[More Information Needed]
### Out-of-Scope Use
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## Bias, Risks, and Limitations
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[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
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#### Preprocessing [optional]
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#### Training Hyperparameters
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#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
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### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
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[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
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## Model Card Authors [optional]
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## Model Card Contact
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### Framework versions
- PEFT 0.12.0 |
BarBarickoza/Magnum-Blackout-Ataraxy-5-9b | BarBarickoza | "2024-09-18T23:31:16Z" | 0 | 1 | transformers | [
"transformers",
"safetensors",
"gemma2",
"text-generation",
"mergekit",
"merge",
"arxiv:2311.03099",
"arxiv:2306.01708",
"base_model:anthracite-org/magnum-v3-9b-customgemma2",
"base_model:merge:anthracite-org/magnum-v3-9b-customgemma2",
"base_model:inflatebot/G2-9B-Blackout-R1",
"base_model:merge:inflatebot/G2-9B-Blackout-R1",
"base_model:lemon07r/Gemma-2-Ataraxy-9B",
"base_model:merge:lemon07r/Gemma-2-Ataraxy-9B",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | "2024-09-18T23:25:43Z" | ---
base_model:
- inflatebot/G2-9B-Blackout-R1
- lemon07r/Gemma-2-Ataraxy-9B
- anthracite-org/magnum-v3-9b-customgemma2
library_name: transformers
tags:
- mergekit
- merge
---
# merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [anthracite-org/magnum-v3-9b-customgemma2](https://huggingface.co/anthracite-org/magnum-v3-9b-customgemma2) as a base.
### Models Merged
The following models were included in the merge:
* [inflatebot/G2-9B-Blackout-R1](https://huggingface.co/inflatebot/G2-9B-Blackout-R1)
* [lemon07r/Gemma-2-Ataraxy-9B](https://huggingface.co/lemon07r/Gemma-2-Ataraxy-9B)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
models:
- model: inflatebot/G2-9B-Blackout-R1
parameters:
weight: 0.6
density: 0.7
- model: lemon07r/Gemma-2-Ataraxy-9B
parameters:
weight: 0.15
density: 0.5
merge_method: dare_ties
base_model: anthracite-org/magnum-v3-9b-customgemma2
tokenizer_source: base
dtype: bfloat16
```
|
DippyAI/Bondds_11-2102grapph | DippyAI | "2024-09-18T23:26:39Z" | 0 | 0 | null | [
"safetensors",
"llama",
"region:us"
] | null | "2024-09-18T23:26:39Z" | Entry not found |
DippyAI/slotomatos_9-27080453-SloTomatos1 | DippyAI | "2024-09-18T23:26:42Z" | 0 | 0 | null | [
"safetensors",
"llama",
"region:us"
] | null | "2024-09-18T23:26:42Z" | Entry not found |
utahnlp/naturalquestionsShort_gpt2-xl_seed-1 | utahnlp | "2024-09-18T23:29:47Z" | 0 | 0 | null | [
"safetensors",
"gpt2",
"region:us"
] | null | "2024-09-18T23:26:43Z" | Entry not found |
DippyAI/slotomatos_19-31082117-SloTomatos1 | DippyAI | "2024-09-18T23:26:45Z" | 0 | 0 | null | [
"safetensors",
"llama",
"region:us"
] | null | "2024-09-18T23:26:45Z" | Entry not found |
DippyAI/starnet_14-star-08-13-00 | DippyAI | "2024-09-18T23:26:48Z" | 0 | 0 | null | [
"safetensors",
"llama",
"region:us"
] | null | "2024-09-18T23:26:48Z" | Entry not found |
DippyAI/denisman_llama-3.1 | DippyAI | "2024-09-18T23:26:51Z" | 0 | 0 | null | [
"safetensors",
"mixtral",
"region:us"
] | null | "2024-09-18T23:26:51Z" | Entry not found |
DippyAI/healtori_11-heal-08-14-08 | DippyAI | "2024-09-18T23:26:54Z" | 0 | 0 | null | [
"safetensors",
"llama",
"region:us"
] | null | "2024-09-18T23:26:54Z" | Entry not found |
DippyAI/slotomatos_15-27081545-SloTomatos1 | DippyAI | "2024-09-18T23:26:57Z" | 0 | 0 | null | [
"safetensors",
"llama",
"region:us"
] | null | "2024-09-18T23:26:57Z" | Entry not found |
DippyAI/denisman_llama-4.31-k-18 | DippyAI | "2024-09-18T23:27:00Z" | 0 | 0 | null | [
"safetensors",
"mixtral",
"region:us"
] | null | "2024-09-18T23:27:00Z" | Entry not found |
DippyAI/healtori_16-heal-08-14-08 | DippyAI | "2024-09-18T23:27:03Z" | 0 | 0 | null | [
"safetensors",
"llama",
"region:us"
] | null | "2024-09-18T23:27:03Z" | Entry not found |
Downtown-Case/Qwen_Qwen2.5-32B-Base-exl2-3.92bpw | Downtown-Case | "2024-09-19T19:46:55Z" | 0 | 1 | null | [
"safetensors",
"qwen2",
"text-generation",
"conversational",
"en",
"base_model:Qwen/Qwen2.5-32B",
"base_model:quantized:Qwen/Qwen2.5-32B",
"license:apache-2.0",
"exl2",
"region:us"
] | text-generation | "2024-09-18T23:27:26Z" | ---
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen2.5-32B/blob/main/LICENSE
language:
- en
pipeline_tag: text-generation
base_model:
- Qwen/Qwen2.5-32B
---
# Quantization
3.92bpw quantization using default settings, for good amount of context on a 24GB GPU.
This is the base model, not instruct! Base models tend to be better for raw completion, especially at long context.
# Qwen2.5-32B
## Introduction
Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:
- Significantly **more knowledge** and has greatly improved capabilities in **coding** and **mathematics**, thanks to our specialized expert models in these domains.
- Significant improvements in **instruction following**, **generating long texts** (over 8K tokens), **understanding structured data** (e.g, tables), and **generating structured outputs** especially JSON. **More resilient to the diversity of system prompts**, enhancing role-play implementation and condition-setting for chatbots.
- **Long-context Support** up to 128K tokens and can generate up to 8K tokens.
- **Multilingual support** for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.
**This repo contains the base 32B Qwen2.5 model**, which has the following features:
- Type: Causal Language Models
- Training Stage: Pretraining
- Architecture: transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias
- Number of Parameters: 32.5B
- Number of Paramaters (Non-Embedding): 31.0B
- Number of Layers: 64
- Number of Attention Heads (GQA): 40 for Q and 8 for KV
- Context Length: 131,072 tokens
**We do not recommend using base language models for conversations.** Instead, you can apply post-training, e.g., SFT, RLHF, continued pretraining, etc., on this model.
For more details, please refer to our [blog](https://qwenlm.github.io/blog/qwen2.5/), [GitHub](https://github.com/QwenLM/Qwen2.5), and [Documentation](https://qwen.readthedocs.io/en/latest/).
## Requirements
The code of Qwen2.5 has been in the latest Hugging face `transformers` and we advise you to use the latest version of `transformers`.
With `transformers<4.37.0`, you will encounter the following error:
```
KeyError: 'qwen2'
```
## Evaluation & Performance
Detailed evaluation results are reported in this [📑 blog](https://qwenlm.github.io/blog/qwen2.5/).
For requirements on GPU memory and the respective throughput, see results [here](https://qwen.readthedocs.io/en/latest/benchmark/speed_benchmark.html).
## Citation
If you find our work helpful, feel free to give us a cite.
```
@misc{qwen2.5,
title = {Qwen2.5: A Party of Foundation Models},
url = {https://qwenlm.github.io/blog/qwen2.5/},
author = {Qwen Team},
month = {September},
year = {2024}
}
@article{qwen2,
title={Qwen2 Technical Report},
author={An Yang and Baosong Yang and Binyuan Hui and Bo Zheng and Bowen Yu and Chang Zhou and Chengpeng Li and Chengyuan Li and Dayiheng Liu and Fei Huang and Guanting Dong and Haoran Wei and Huan Lin and Jialong Tang and Jialin Wang and Jian Yang and Jianhong Tu and Jianwei Zhang and Jianxin Ma and Jin Xu and Jingren Zhou and Jinze Bai and Jinzheng He and Junyang Lin and Kai Dang and Keming Lu and Keqin Chen and Kexin Yang and Mei Li and Mingfeng Xue and Na Ni and Pei Zhang and Peng Wang and Ru Peng and Rui Men and Ruize Gao and Runji Lin and Shijie Wang and Shuai Bai and Sinan Tan and Tianhang Zhu and Tianhao Li and Tianyu Liu and Wenbin Ge and Xiaodong Deng and Xiaohuan Zhou and Xingzhang Ren and Xinyu Zhang and Xipin Wei and Xuancheng Ren and Yang Fan and Yang Yao and Yichang Zhang and Yu Wan and Yunfei Chu and Yuqiong Liu and Zeyu Cui and Zhenru Zhang and Zhihao Fan},
journal={arXiv preprint arXiv:2407.10671},
year={2024}
}
``` |
Krabat/google-gemma-2b-1726702059 | Krabat | "2024-09-18T23:27:43Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-18T23:27:39Z" | ---
base_model: google/gemma-2b
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
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### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
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[More Information Needed]
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#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
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<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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[More Information Needed]
**APA:**
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## Glossary [optional]
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## Model Card Contact
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### Framework versions
- PEFT 0.12.0 |
noxneural/ActGen | noxneural | "2024-09-18T23:57:02Z" | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | "2024-09-18T23:27:41Z" | Entry not found |
SALUTEASD/Qwen-Qwen1.5-1.8B-1726702115 | SALUTEASD | "2024-09-18T23:28:41Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-18T23:28:33Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
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[More Information Needed]
#### Factors
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#### Metrics
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[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
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## Technical Specifications [optional]
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[More Information Needed]
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[More Information Needed]
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### Framework versions
- PEFT 0.12.0 |
dogssss/Qwen-Qwen1.5-1.8B-1726702125 | dogssss | "2024-09-18T23:28:49Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-18T23:28:45Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
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[More Information Needed]
## Training Details
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#### Summary
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## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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### Framework versions
- PEFT 0.12.0 |
jwu205/distilbert-base-uncased-finetuned-ner | jwu205 | "2024-09-19T20:33:10Z" | 0 | 0 | null | [
"pytorch",
"distilbert",
"generated_from_trainer",
"dataset:conll2003",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"model-index",
"region:us"
] | null | "2024-09-18T23:29:17Z" | ---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
config: conll2003
split: validation
args: conll2003
metrics:
- name: Precision
type: precision
value: 0.9306140545333629
- name: Recall
type: recall
value: 0.9392549502181452
- name: F1
type: f1
value: 0.9349145370525026
- name: Accuracy
type: accuracy
value: 0.9842248240583348
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-ner
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0664
- Precision: 0.9306
- Recall: 0.9393
- F1: 0.9349
- Accuracy: 0.9842
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0525 | 1.0 | 878 | 0.0671 | 0.9121 | 0.9308 | 0.9213 | 0.9820 |
| 0.0287 | 2.0 | 1756 | 0.0640 | 0.9281 | 0.9361 | 0.9321 | 0.9838 |
| 0.0169 | 3.0 | 2634 | 0.0664 | 0.9306 | 0.9393 | 0.9349 | 0.9842 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.2.1+cpu
- Datasets 2.21.0
- Tokenizers 0.13.2
|
tronsdds/google-gemma-7b-1726702176 | tronsdds | "2024-09-18T23:30:25Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-7b",
"base_model:adapter:google/gemma-7b",
"region:us"
] | null | "2024-09-18T23:29:36Z" | ---
base_model: google/gemma-7b
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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### Recommendations
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
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[More Information Needed]
## Training Details
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[More Information Needed]
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## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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### Framework versions
- PEFT 0.12.0 |
utahnlp/naturalquestionsShort_gpt2-xl_seed-2 | utahnlp | "2024-09-18T23:33:12Z" | 0 | 0 | null | [
"safetensors",
"gpt2",
"region:us"
] | null | "2024-09-18T23:30:12Z" | Entry not found |
huazi123/google-gemma-2b-1726702231 | huazi123 | "2024-09-18T23:30:35Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-18T23:30:29Z" | ---
base_model: google/gemma-2b
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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[More Information Needed]
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<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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## Technical Specifications [optional]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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Krabat/google-gemma-7b-1726702263 | Krabat | "2024-09-18T23:31:07Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-7b",
"base_model:adapter:google/gemma-7b",
"region:us"
] | null | "2024-09-18T23:31:03Z" | ---
base_model: google/gemma-7b
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
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[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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### Framework versions
- PEFT 0.12.0 |
aang77/vocano | aang77 | "2024-09-18T23:31:42Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-18T23:31:42Z" | Entry not found |
tronsdds/Qwen-Qwen1.5-1.8B-1726702310 | tronsdds | "2024-09-18T23:32:02Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-18T23:31:50Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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[More Information Needed]
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dogssss/Qwen-Qwen1.5-0.5B-1726702400 | dogssss | "2024-09-18T23:33:25Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-18T23:33:21Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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rana-shahroz/mistral-7b-openorca-lora-r8-rte-epochs5-adapter | rana-shahroz | "2024-09-18T23:33:35Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | "2024-09-18T23:33:32Z" | ---
library_name: transformers
tags: []
---
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utahnlp/naturalquestionsShort_gpt2-xl_seed-3 | utahnlp | "2024-09-18T23:36:42Z" | 0 | 0 | null | [
"safetensors",
"gpt2",
"region:us"
] | null | "2024-09-18T23:33:35Z" | Entry not found |
tronsdds/google-gemma-2b-1726702418 | tronsdds | "2024-09-18T23:34:13Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-18T23:33:39Z" | ---
base_model: google/gemma-2b
library_name: peft
---
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huazi123/Qwen-Qwen1.5-0.5B-1726702445 | huazi123 | "2024-09-18T23:34:07Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-18T23:34:03Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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