Instructions to use mlx-community/CodeLlama-7b-Python-hf-8bit-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-hf-8bit-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-hf-8bit-mlx") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- MLX LM
How to use mlx-community/CodeLlama-7b-Python-hf-8bit-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-hf-8bit-mlx" --prompt "Once upon a time"
- Xet hash:
- cd00432c10b0d1954ff4c3618d83eb95f1143c3b3e8e7c5e3067d70c7a8c8137
- Size of remote file:
- 7.28 GB
- SHA256:
- b8e7d193ab62d2e81e0d9aad21975ee68372048664ff1ffa81df3803f8d4eb71
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