| license: apache-2.0 | |
| base_model: unsloth/SmolLM-360M | |
| tags: | |
| - alignment-handbook | |
| - trl | |
| - unsloth | |
| - mlx | |
| datasets: | |
| - Magpie-Align/Magpie-Pro-300K-Filtered | |
| - bigcode/self-oss-instruct-sc2-exec-filter-50k | |
| - teknium/OpenHermes-2.5 | |
| - HuggingFaceTB/everyday-conversations-llama3.1-2k | |
| library_name: transformers | |
| language: | |
| - en | |
| # shashikanth-a/SmolLM-360M-4bit | |
| The Model [shashikanth-a/SmolLM-360M-4bit](https://huggingface.co/shashikanth-a/SmolLM-360M-4bit) was converted to MLX format from [unsloth/SmolLM-360M](https://huggingface.co/unsloth/SmolLM-360M) using mlx-lm version **0.19.3**. | |
| ## Use with mlx | |
| ```bash | |
| pip install mlx-lm | |
| ``` | |
| ```python | |
| from mlx_lm import load, generate | |
| model, tokenizer = load("shashikanth-a/SmolLM-360M-4bit") | |
| 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) | |
| ``` | |