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--- |
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language: |
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- en |
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- ko |
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library_name: transformers |
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tags: |
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- pytorch |
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- Yi-Ko |
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- 01-ai |
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- Yi |
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- TensorBlock |
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- GGUF |
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extra_gated_heading: Access beomi/Yi-Ko-6B on Hugging Face |
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extra_gated_button_content: Submit |
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extra_gated_fields: |
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I agree to share my name, email address and username: checkbox |
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? I confirm that I understand this project is for research purposes only, and confirm |
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that I agree to follow the LICENSE of this model |
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: checkbox |
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pipeline_tag: text-generation |
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inference: false |
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license: apache-2.0 |
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base_model: beomi/Yi-Ko-6B |
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model-index: |
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- name: Yi-Ko-6B |
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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: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 48.89 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beomi/Yi-Ko-6B |
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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: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 74.48 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beomi/Yi-Ko-6B |
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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 (5-Shot) |
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type: cais/mmlu |
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config: all |
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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: 55.72 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beomi/Yi-Ko-6B |
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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: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 37.09 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beomi/Yi-Ko-6B |
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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: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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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: 72.93 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beomi/Yi-Ko-6B |
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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: GSM8k (5-shot) |
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type: gsm8k |
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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: 12.51 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=beomi/Yi-Ko-6B |
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name: Open LLM Leaderboard |
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--- |
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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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|
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## beomi/Yi-Ko-6B - GGUF |
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This repo contains GGUF format model files for [beomi/Yi-Ko-6B](https://huggingface.co/beomi/Yi-Ko-6B). |
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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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## Prompt template |
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``` |
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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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| [Yi-Ko-6B-Q2_K.gguf](https://huggingface.co/tensorblock/Yi-Ko-6B-GGUF/tree/main/Yi-Ko-6B-Q2_K.gguf) | Q2_K | 2.240 GB | smallest, significant quality loss - not recommended for most purposes | |
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| [Yi-Ko-6B-Q3_K_S.gguf](https://huggingface.co/tensorblock/Yi-Ko-6B-GGUF/tree/main/Yi-Ko-6B-Q3_K_S.gguf) | Q3_K_S | 2.592 GB | very small, high quality loss | |
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| [Yi-Ko-6B-Q3_K_M.gguf](https://huggingface.co/tensorblock/Yi-Ko-6B-GGUF/tree/main/Yi-Ko-6B-Q3_K_M.gguf) | Q3_K_M | 2.857 GB | very small, high quality loss | |
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| [Yi-Ko-6B-Q3_K_L.gguf](https://huggingface.co/tensorblock/Yi-Ko-6B-GGUF/tree/main/Yi-Ko-6B-Q3_K_L.gguf) | Q3_K_L | 3.084 GB | small, substantial quality loss | |
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| [Yi-Ko-6B-Q4_0.gguf](https://huggingface.co/tensorblock/Yi-Ko-6B-GGUF/tree/main/Yi-Ko-6B-Q4_0.gguf) | Q4_0 | 3.317 GB | legacy; small, very high quality loss - prefer using Q3_K_M | |
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| [Yi-Ko-6B-Q4_K_S.gguf](https://huggingface.co/tensorblock/Yi-Ko-6B-GGUF/tree/main/Yi-Ko-6B-Q4_K_S.gguf) | Q4_K_S | 3.339 GB | small, greater quality loss | |
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| [Yi-Ko-6B-Q4_K_M.gguf](https://huggingface.co/tensorblock/Yi-Ko-6B-GGUF/tree/main/Yi-Ko-6B-Q4_K_M.gguf) | Q4_K_M | 3.498 GB | medium, balanced quality - recommended | |
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| [Yi-Ko-6B-Q5_0.gguf](https://huggingface.co/tensorblock/Yi-Ko-6B-GGUF/tree/main/Yi-Ko-6B-Q5_0.gguf) | Q5_0 | 3.999 GB | legacy; medium, balanced quality - prefer using Q4_K_M | |
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| [Yi-Ko-6B-Q5_K_S.gguf](https://huggingface.co/tensorblock/Yi-Ko-6B-GGUF/tree/main/Yi-Ko-6B-Q5_K_S.gguf) | Q5_K_S | 3.999 GB | large, low quality loss - recommended | |
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| [Yi-Ko-6B-Q5_K_M.gguf](https://huggingface.co/tensorblock/Yi-Ko-6B-GGUF/tree/main/Yi-Ko-6B-Q5_K_M.gguf) | Q5_K_M | 4.092 GB | large, very low quality loss - recommended | |
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| [Yi-Ko-6B-Q6_K.gguf](https://huggingface.co/tensorblock/Yi-Ko-6B-GGUF/tree/main/Yi-Ko-6B-Q6_K.gguf) | Q6_K | 4.724 GB | very large, extremely low quality loss | |
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| [Yi-Ko-6B-Q8_0.gguf](https://huggingface.co/tensorblock/Yi-Ko-6B-GGUF/tree/main/Yi-Ko-6B-Q8_0.gguf) | Q8_0 | 6.117 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/Yi-Ko-6B-GGUF --include "Yi-Ko-6B-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/Yi-Ko-6B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' |
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``` |
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