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  <!-- ### quantize_version: 2 -->
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  <!-- ### output_tensor_quantised: 1 -->
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  <!-- ### convert_type: hf -->
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  <!-- ### vocab_type: -->
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  <!-- ### tags: nicoboss -->
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  weighted/imatrix quants of https://huggingface.co/Weyaxi/Einstein-v7-Qwen2-7B
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ base_model: Weyaxi/Einstein-v7-Qwen2-7B
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+ datasets:
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+ - allenai/ai2_arc
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+ - camel-ai/physics
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+ - camel-ai/chemistry
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+ - camel-ai/biology
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+ - camel-ai/math
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+ - metaeval/reclor
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+ - openbookqa
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+ - mandyyyyii/scibench
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+ - derek-thomas/ScienceQA
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+ - TIGER-Lab/ScienceEval
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+ - jondurbin/airoboros-3.2
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+ - LDJnr/Capybara
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+ - Cot-Alpaca-GPT4-From-OpenHermes-2.5
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+ - STEM-AI-mtl/Electrical-engineering
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+ - knowrohit07/saraswati-stem
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+ - sablo/oasst2_curated
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+ - lmsys/lmsys-chat-1m
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+ - TIGER-Lab/MathInstruct
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+ - bigbio/med_qa
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+ - meta-math/MetaMathQA-40K
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+ - openbookqa
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+ - piqa
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+ - metaeval/reclor
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+ - derek-thomas/ScienceQA
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+ - scibench
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+ - sciq
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+ - Open-Orca/SlimOrca
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+ - migtissera/Synthia-v1.3
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+ - TIGER-Lab/ScienceEval
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+ - allenai/WildChat
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+ - microsoft/orca-math-word-problems-200k
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+ - openchat/openchat_sharegpt4_dataset
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+ - teknium/GPTeacher-General-Instruct
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+ - m-a-p/CodeFeedback-Filtered-Instruction
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+ - totally-not-an-llm/EverythingLM-data-V3
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+ - HuggingFaceH4/no_robots
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+ - OpenAssistant/oasst_top1_2023-08-25
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+ - WizardLM/WizardLM_evol_instruct_70k
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+ - abacusai/SystemChat-1.1
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+ - H-D-T/Buzz-V1.2
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+ language:
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+ - en
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+ library_name: transformers
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+ license: other
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+ quantized_by: mradermacher
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+ tags:
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+ - axolotl
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+ - instruct
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+ - finetune
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+ - chatml
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+ - gpt4
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+ - synthetic data
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+ - science
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+ - physics
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+ - chemistry
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+ - biology
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+ - math
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+ - qwen
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+ - qwen2
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+ ---
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+ ## About
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+
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  <!-- ### quantize_version: 2 -->
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  <!-- ### output_tensor_quantised: 1 -->
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  <!-- ### convert_type: hf -->
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  <!-- ### vocab_type: -->
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  <!-- ### tags: nicoboss -->
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  weighted/imatrix quants of https://huggingface.co/Weyaxi/Einstein-v7-Qwen2-7B
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+
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+ <!-- provided-files -->
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+ static quants are available at https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF
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+ ## Usage
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+
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+ If you are unsure how to use GGUF files, refer to one of [TheBloke's
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+ READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
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+ more details, including on how to concatenate multi-part files.
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+
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+ ## Provided Quants
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+
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+ (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
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+
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+ | Link | Type | Size/GB | Notes |
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+ |:-----|:-----|--------:|:------|
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-IQ1_S.gguf) | i1-IQ1_S | 2.0 | for the desperate |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-IQ1_M.gguf) | i1-IQ1_M | 2.1 | mostly desperate |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.4 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.6 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-IQ2_S.gguf) | i1-IQ2_S | 2.7 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-IQ2_M.gguf) | i1-IQ2_M | 2.9 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-Q2_K.gguf) | i1-Q2_K | 3.1 | IQ3_XXS probably better |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.2 | lower quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.4 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.6 | IQ3_XS probably better |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-IQ3_S.gguf) | i1-IQ3_S | 3.6 | beats Q3_K* |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-IQ3_M.gguf) | i1-IQ3_M | 3.7 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 3.9 | IQ3_S probably better |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 4.2 | IQ3_M probably better |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.3 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-Q4_0.gguf) | i1-Q4_0 | 4.5 | fast, low quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.6 | optimal size/speed/quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 4.8 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.4 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.5 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF/resolve/main/Einstein-v7-Qwen2-7B.i1-Q6_K.gguf) | i1-Q6_K | 6.4 | practically like static Q6_K |
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+
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+ Here is a handy graph by ikawrakow comparing some lower-quality quant
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+ types (lower is better):
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+
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+ ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
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+
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+ And here are Artefact2's thoughts on the matter:
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+ https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
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+
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+ ## FAQ / Model Request
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+
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+ See https://huggingface.co/mradermacher/model_requests for some answers to
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+ questions you might have and/or if you want some other model quantized.
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+
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+ ## Thanks
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+
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+ I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
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+ me use its servers and providing upgrades to my workstation to enable
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+ this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his hardware for calculating the imatrix for these quants.
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+
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+ <!-- end -->