Instructions to use mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir DeepSeek-Coder-V2-Lite-Instruct-4bit-mlx mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-mlx
The Model mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-mlx was converted to MLX format from deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct using mlx-lm version 0.16.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-mlx")
response = generate(model, tokenizer, prompt="hello", verbose=True)
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Model size
2B params
Tensor type
F16
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U32 ·
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# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir DeepSeek-Coder-V2-Lite-Instruct-4bit-mlx mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-mlx