Instructions to use mlx-community/functionary-small-v3.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/functionary-small-v3.2 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/functionary-small-v3.2 --local-dir functionary-small-v3.2
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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Download README.md from mlx-community/functionary-small-v3.2: direct link, hf CLI and curl.
- Browser
- Download file 879 Bytes
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https://huggingface.co/mlx-community/functionary-small-v3.2/resolve/main/README.md
- Command line
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hf download hf://mlx-community/functionary-small-v3.2/README.md
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curl -L -o README.md https://huggingface.co/mlx-community/functionary-small-v3.2/resolve/main/README.md
879 Bytes
| base_model: meetkai/functionary-small-v3.2 | |
| license: mit | |
| tags: | |
| - mlx | |
| # mlx-community/functionary-small-v3.2 | |
| The Model [mlx-community/functionary-small-v3.2](https://huggingface.co/mlx-community/functionary-small-v3.2) was | |
| converted to MLX format from [meetkai/functionary-small-v3.2](https://huggingface.co/meetkai/functionary-small-v3.2) | |
| using mlx-lm version **0.20.1**. | |
| ## Use with mlx | |
| ```bash | |
| pip install mlx-lm | |
| ``` | |
| ```python | |
| from mlx_lm import load, generate | |
| model, tokenizer = load("mlx-community/functionary-small-v3.2") | |
| 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) | |
| ``` | |