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--- |
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language: |
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- zh |
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- en |
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license: gpl-3.0 |
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tags: |
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- qwen |
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- uncensored |
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- mlx |
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base_model: Orion-zhen/Qwen2.5-7B-Instruct-Uncensored |
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datasets: |
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- NobodyExistsOnTheInternet/ToxicQAFinal |
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- anthracite-org/kalo-opus-instruct-22k-no-refusal |
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- Orion-zhen/dpo-toxic-zh |
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- unalignment/toxic-dpo-v0.2 |
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- Crystalcareai/Intel-DPO-Pairs-Norefusals |
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pipeline_tag: text-generation |
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model-index: |
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- name: Qwen2.5-7B-Instruct-Uncensored |
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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: 72.04 |
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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=Orion-zhen/Qwen2.5-7B-Instruct-Uncensored |
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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: 35.83 |
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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=Orion-zhen/Qwen2.5-7B-Instruct-Uncensored |
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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: 1.36 |
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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=Orion-zhen/Qwen2.5-7B-Instruct-Uncensored |
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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: 7.05 |
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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=Orion-zhen/Qwen2.5-7B-Instruct-Uncensored |
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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: 13.58 |
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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=Orion-zhen/Qwen2.5-7B-Instruct-Uncensored |
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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: 38.07 |
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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=Orion-zhen/Qwen2.5-7B-Instruct-Uncensored |
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name: Open LLM Leaderboard |
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--- |
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# mlx-community/Qwen2.5-7B-Instruct-Uncensored-4bit |
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The Model [mlx-community/Qwen2.5-7B-Instruct-Uncensored-4bit](https://huggingface.co/mlx-community/Qwen2.5-7B-Instruct-Uncensored-4bit) was converted to MLX format from [Orion-zhen/Qwen2.5-7B-Instruct-Uncensored](https://huggingface.co/Orion-zhen/Qwen2.5-7B-Instruct-Uncensored) using mlx-lm version **0.19.1**. |
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## Use with mlx |
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```bash |
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pip install mlx-lm |
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``` |
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```python |
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from mlx_lm import load, generate |
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model, tokenizer = load("mlx-community/Qwen2.5-7B-Instruct-Uncensored-4bit") |
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prompt="hello" |
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if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None: |
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messages = [{"role": "user", "content": prompt}] |
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prompt = tokenizer.apply_chat_template( |
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messages, tokenize=False, add_generation_prompt=True |
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) |
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response = generate(model, tokenizer, prompt=prompt, verbose=True) |
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``` |
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