123 lines
4.7 KiB
Markdown
123 lines
4.7 KiB
Markdown
---
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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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<!-- ### 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: -->
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static quants of https://huggingface.co/Weyaxi/Einstein-v7-Qwen2-7B
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<!-- provided-files -->
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weighted/imatrix quants are available at https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-i1-GGUF
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## Usage
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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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## Provided Quants
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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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| Link | Type | Size/GB | Notes |
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|:-----|:-----|--------:|:------|
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.Q2_K.gguf) | Q2_K | 3.1 | |
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.IQ3_XS.gguf) | IQ3_XS | 3.4 | |
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.Q3_K_S.gguf) | Q3_K_S | 3.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.IQ3_S.gguf) | IQ3_S | 3.6 | beats Q3_K* |
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.IQ3_M.gguf) | IQ3_M | 3.7 | |
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.Q3_K_L.gguf) | Q3_K_L | 4.2 | |
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.IQ4_XS.gguf) | IQ4_XS | 4.4 | |
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.Q4_K_S.gguf) | Q4_K_S | 4.6 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.Q4_K_M.gguf) | Q4_K_M | 4.8 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.Q5_K_S.gguf) | Q5_K_S | 5.4 | |
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.Q5_K_M.gguf) | Q5_K_M | 5.5 | |
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.Q6_K.gguf) | Q6_K | 6.4 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.Q8_0.gguf) | Q8_0 | 8.2 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/Einstein-v7-Qwen2-7B-GGUF/resolve/main/Einstein-v7-Qwen2-7B.f16.gguf) | f16 | 15.3 | 16 bpw, overkill |
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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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And here are Artefact2's thoughts on the matter:
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https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
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## FAQ / Model Request
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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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## Thanks
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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.
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<!-- end -->
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