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mradermacher
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Einstein-v7-Qwen2-7B-i1-GGUF

Transformers
GGUF
40 datasets
English
axolotl
instruct
finetune
chatml
gpt4
synthetic data
science
physics
chemistry
biology
math
qwen
qwen2
Inference Endpoints
imatrix
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metadata
base_model: Weyaxi/Einstein-v7-Qwen2-7B
datasets:
  - allenai/ai2_arc
  - camel-ai/physics
  - camel-ai/chemistry
  - camel-ai/biology
  - camel-ai/math
  - metaeval/reclor
  - openbookqa
  - mandyyyyii/scibench
  - derek-thomas/ScienceQA
  - TIGER-Lab/ScienceEval
  - jondurbin/airoboros-3.2
  - LDJnr/Capybara
  - Cot-Alpaca-GPT4-From-OpenHermes-2.5
  - STEM-AI-mtl/Electrical-engineering
  - knowrohit07/saraswati-stem
  - sablo/oasst2_curated
  - lmsys/lmsys-chat-1m
  - TIGER-Lab/MathInstruct
  - bigbio/med_qa
  - meta-math/MetaMathQA-40K
  - openbookqa
  - piqa
  - metaeval/reclor
  - derek-thomas/ScienceQA
  - scibench
  - sciq
  - Open-Orca/SlimOrca
  - migtissera/Synthia-v1.3
  - TIGER-Lab/ScienceEval
  - allenai/WildChat
  - microsoft/orca-math-word-problems-200k
  - openchat/openchat_sharegpt4_dataset
  - teknium/GPTeacher-General-Instruct
  - m-a-p/CodeFeedback-Filtered-Instruction
  - totally-not-an-llm/EverythingLM-data-V3
  - HuggingFaceH4/no_robots
  - OpenAssistant/oasst_top1_2023-08-25
  - WizardLM/WizardLM_evol_instruct_70k
  - abacusai/SystemChat-1.1
  - H-D-T/Buzz-V1.2
language:
  - en
library_name: transformers
license: other
quantized_by: mradermacher
tags:
  - axolotl
  - instruct
  - finetune
  - chatml
  - gpt4
  - synthetic data
  - science
  - physics
  - chemistry
  - biology
  - math
  - qwen
  - qwen2

About

weighted/imatrix quants of https://huggingface.co/Weyaxi/Einstein-v7-Qwen2-7B

static quants are available at https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
GGUF i1-IQ1_S 2.0 for the desperate
GGUF i1-IQ1_M 2.1 mostly desperate
GGUF i1-IQ2_XXS 2.4
GGUF i1-IQ2_XS 2.6
GGUF i1-IQ2_S 2.7
GGUF i1-IQ2_M 2.9
GGUF i1-Q2_K 3.1 IQ3_XXS probably better
GGUF i1-IQ3_XXS 3.2 lower quality
GGUF i1-IQ3_XS 3.4
GGUF i1-Q3_K_S 3.6 IQ3_XS probably better
GGUF i1-IQ3_S 3.6 beats Q3_K*
GGUF i1-IQ3_M 3.7
GGUF i1-Q3_K_M 3.9 IQ3_S probably better
GGUF i1-Q3_K_L 4.2 IQ3_M probably better
GGUF i1-IQ4_XS 4.3
GGUF i1-Q4_0 4.5 fast, low quality
GGUF i1-Q4_K_S 4.6 optimal size/speed/quality
GGUF i1-Q4_K_M 4.8 fast, recommended
GGUF i1-Q5_K_S 5.4
GGUF i1-Q5_K_M 5.5
GGUF i1-Q6_K 6.4 practically like static Q6_K

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.png

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.