Instructions to use mlx-community/CodeLlama-7b-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/CodeLlama-7b-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-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-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-mlx" --prompt "Once upon a time"
- Atomic Chat
Commit History
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Remove library
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Merge remote-tracking branch 'origin/main' into pr/5
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Add library_name
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Update README.md (#6)
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params.json -> config.json, add model_type
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License field (#4)
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Fix code snippet (#3)
- Fix code snippet (84d31437652a5b2b881f2d7a1c31c8322e2573a8)44c95ab
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update to new format
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Update usage instructions (#2)
- Update usage instructions (effcc2d4937955797f4ac5349b6df02aea490ed1)7423696 -
Upload folder using huggingface_hub (#1)
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initial commit
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