--- language: - en - de license: apache-2.0 tags: - chat - mlx base_model: Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4 license_link: https://huggingface.co/Qwen/Qwen2.5-14B-Instruct/blob/main/LICENSE pipeline_tag: text-generation model-index: - name: Josiefied-Qwen2.5-14B-Instruct-abliterated-v4 results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 82.92 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics: - type: acc_norm value: 48.05 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics: - type: exact_match value: 0.0 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics: - type: acc_norm value: 12.3 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics: - type: acc_norm value: 13.15 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 44.65 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4 name: Open LLM Leaderboard --- # mlx-community/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-8-bit The Model [mlx-community/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-8-bit](https://huggingface.co/mlx-community/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-8-bit) was converted to MLX format from [Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4](https://huggingface.co/Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4) using mlx-lm version **0.20.2**. ## Use with mlx ```bash pip install mlx-lm ``` ```python from mlx_lm import load, generate model, tokenizer = load("mlx-community/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-8-bit") prompt="hello" if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None: messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, tokenize=False, add_generation_prompt=True ) response = generate(model, tokenizer, prompt=prompt, verbose=True) ```