1.2 KiB
Deepseek Coder
Deepseek Coder is a family of code generating language models based on the Llama architecture.1 The models were trained from scratch on a corpus of 2T tokens, with a composition of 87% code and 13% natural language containing both English and Chinese.
Setup
Install the dependencies:
pip install -r requirements.txt
Next, download and convert the model.
python convert.py --hf-path <path_to_huggingface_model>
To generate a 4-bit quantized model, use -q. For a full list of options run:
python convert.py --help
The converter downloads the model from Hugging Face. The default model is
deepseek-ai/deepseek-coder-6.7b-instruct. Check out the [Hugging Face
page]((https://huggingface.co/deepseek-ai) to see a list of available models.
By default, the conversion script will save the converted weights.npz,
tokenizer, and config.json in the mlx_model directory.
Run
Once you've converted the weights, you can interact with the Deepseek coder model:
python deepseek_coder.py --prompt "write a quick sort algorithm in python."