--- license: other license_name: qwen license_link: https://huggingface.co/skt/A.X-4.0/blob/main/LICENSE language: - en - ko pipeline_tag: text-generation library_name: mlx model_id: skt/A.X-4.0 developers: SKT AI Model Lab tags: - mlx base_model: skt/A.X-4.0 model-index: - name: A.X-4.0 results: - task: type: generate_until name: mmlu dataset: name: mmlu (chat CoT) type: hails/mmlu_no_train metrics: - type: exact_match value: 86.62 name: exact_match - task: type: generate_until name: kmmlu dataset: name: kmmlu (chat CoT) type: HAERAE-HUB/KMMLU metrics: - type: exact_match value: 78.32 name: exact_match --- # litmudoc/A.X-4.0-72B-MLX-Q8 This model [litmudoc/A.X-4.0-72B-MLX-Q8](https://huggingface.co/litmudoc/A.X-4.0-72B-MLX-Q8) was converted to MLX format from [skt/A.X-4.0](https://huggingface.co/skt/A.X-4.0) using mlx-lm version **0.25.3**. ## Use with mlx ```bash pip install mlx-lm ``` ```python from mlx_lm import load, generate model, tokenizer = load("litmudoc/A.X-4.0-72B-MLX-Q8") prompt = "hello" if tokenizer.chat_template is not None: messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) response = generate(model, tokenizer, prompt=prompt, verbose=True) ```