Instructions to use mlx-community/CodeLlama-7b-Python-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/CodeLlama-7b-Python-mlx with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("mlx-community/CodeLlama-7b-Python-mlx") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use mlx-community/CodeLlama-7b-Python-mlx with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "mlx-community/CodeLlama-7b-Python-mlx" --prompt "Once upon a time"
- Atomic Chat
Commit History
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config-json (#5)
- params.json -> config.json, add model_type (cdc1b23591e85e76154da58d625369cee5cafab7) - Add library_name (07742ef9f7135415fc9944a8b585dc7bbb121a56) - Merge remote-tracking branch 'origin/main' into pr/5 (d3eecfe113f5d0ffd091fa62f4dcd2fa72dafd58) - Remove library (932d582d11af5cd3fc69817dd54b6283ffd020f3)fc02430