| language: | |
| - en | |
| - ja | |
| library_name: mlx | |
| pipeline_tag: text-generation | |
| license: | |
| - llama3.3 | |
| - gemma | |
| model_type: llama | |
| datasets: | |
| - tokyotech-llm/lmsys-chat-1m-synth | |
| - lmsys/lmsys-chat-1m | |
| base_model: tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.5 | |
| tags: | |
| - mlx | |
| # mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.5 | |
| This model [mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.5](https://huggingface.co/mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.5) was | |
| converted to MLX format from [tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.5](https://huggingface.co/tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.5) | |
| using mlx-lm version **0.25.2**. | |
| ## Use with mlx | |
| ```bash | |
| pip install mlx-lm | |
| ``` | |
| ```python | |
| from mlx_lm import load, generate | |
| model, tokenizer = load("mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.5") | |
| 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) | |
| ``` | |