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--- |
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language: |
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- en |
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license: other |
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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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- TensorBlock |
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- GGUF |
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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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model-index: |
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- name: Einstein-v7-Qwen2-7B |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: IFEval (0-Shot) |
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type: HuggingFaceH4/ifeval |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: inst_level_strict_acc and prompt_level_strict_acc |
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value: 41.0 |
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name: strict accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Weyaxi/Einstein-v7-Qwen2-7B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: BBH (3-Shot) |
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type: BBH |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc_norm |
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value: 32.84 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Weyaxi/Einstein-v7-Qwen2-7B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MATH Lvl 5 (4-Shot) |
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type: hendrycks/competition_math |
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args: |
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num_few_shot: 4 |
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metrics: |
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- type: exact_match |
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value: 15.18 |
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name: exact match |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Weyaxi/Einstein-v7-Qwen2-7B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GPQA (0-shot) |
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type: Idavidrein/gpqa |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 6.6 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Weyaxi/Einstein-v7-Qwen2-7B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MuSR (0-shot) |
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type: TAUR-Lab/MuSR |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 14.06 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Weyaxi/Einstein-v7-Qwen2-7B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU-PRO (5-shot) |
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type: TIGER-Lab/MMLU-Pro |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 34.4 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Weyaxi/Einstein-v7-Qwen2-7B |
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name: Open LLM Leaderboard |
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--- |
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<div style="width: auto; margin-left: auto; margin-right: auto"> |
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<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;"> |
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</div> |
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<div style="display: flex; justify-content: space-between; width: 100%;"> |
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<div style="display: flex; flex-direction: column; align-items: flex-start;"> |
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<p style="margin-top: 0.5em; margin-bottom: 0em;"> |
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Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a> |
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</p> |
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</div> |
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</div> |
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## Weyaxi/Einstein-v7-Qwen2-7B - GGUF |
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This repo contains GGUF format model files for [Weyaxi/Einstein-v7-Qwen2-7B](https://huggingface.co/Weyaxi/Einstein-v7-Qwen2-7B). |
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The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d). |
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<div style="text-align: left; margin: 20px 0;"> |
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<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;"> |
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Run them on the TensorBlock client using your local machine ↗ |
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</a> |
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</div> |
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## Prompt template |
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``` |
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<|im_start|>system |
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{system_prompt}<|im_end|> |
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<|im_start|>user |
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{prompt}<|im_end|> |
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<|im_start|>assistant |
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``` |
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## Model file specification |
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| Filename | Quant type | File Size | Description | |
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| -------- | ---------- | --------- | ----------- | |
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| [Einstein-v7-Qwen2-7B-Q2_K.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q2_K.gguf) | Q2_K | 2.809 GB | smallest, significant quality loss - not recommended for most purposes | |
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| [Einstein-v7-Qwen2-7B-Q3_K_S.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q3_K_S.gguf) | Q3_K_S | 3.253 GB | very small, high quality loss | |
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| [Einstein-v7-Qwen2-7B-Q3_K_M.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q3_K_M.gguf) | Q3_K_M | 3.547 GB | very small, high quality loss | |
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| [Einstein-v7-Qwen2-7B-Q3_K_L.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q3_K_L.gguf) | Q3_K_L | 3.808 GB | small, substantial quality loss | |
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| [Einstein-v7-Qwen2-7B-Q4_0.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q4_0.gguf) | Q4_0 | 4.127 GB | legacy; small, very high quality loss - prefer using Q3_K_M | |
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| [Einstein-v7-Qwen2-7B-Q4_K_S.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q4_K_S.gguf) | Q4_K_S | 4.152 GB | small, greater quality loss | |
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| [Einstein-v7-Qwen2-7B-Q4_K_M.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q4_K_M.gguf) | Q4_K_M | 4.361 GB | medium, balanced quality - recommended | |
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| [Einstein-v7-Qwen2-7B-Q5_0.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q5_0.gguf) | Q5_0 | 4.950 GB | legacy; medium, balanced quality - prefer using Q4_K_M | |
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| [Einstein-v7-Qwen2-7B-Q5_K_S.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q5_K_S.gguf) | Q5_K_S | 4.950 GB | large, low quality loss - recommended | |
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| [Einstein-v7-Qwen2-7B-Q5_K_M.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q5_K_M.gguf) | Q5_K_M | 5.071 GB | large, very low quality loss - recommended | |
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| [Einstein-v7-Qwen2-7B-Q6_K.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q6_K.gguf) | Q6_K | 5.825 GB | very large, extremely low quality loss | |
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| [Einstein-v7-Qwen2-7B-Q8_0.gguf](https://huggingface.co/tensorblock/Einstein-v7-Qwen2-7B-GGUF/blob/main/Einstein-v7-Qwen2-7B-Q8_0.gguf) | Q8_0 | 7.542 GB | very large, extremely low quality loss - not recommended | |
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## Downloading instruction |
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### Command line |
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Firstly, install Huggingface Client |
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```shell |
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pip install -U "huggingface_hub[cli]" |
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``` |
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Then, downoad the individual model file the a local directory |
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```shell |
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huggingface-cli download tensorblock/Einstein-v7-Qwen2-7B-GGUF --include "Einstein-v7-Qwen2-7B-Q2_K.gguf" --local-dir MY_LOCAL_DIR |
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``` |
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If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try: |
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```shell |
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huggingface-cli download tensorblock/Einstein-v7-Qwen2-7B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' |
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``` |
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