Instructions to use nafisabdkhan/DeepSeek-Coder-V2-Instruct-mlx-2Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use nafisabdkhan/DeepSeek-Coder-V2-Instruct-mlx-2Bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir DeepSeek-Coder-V2-Instruct-mlx-2Bit nafisabdkhan/DeepSeek-Coder-V2-Instruct-mlx-2Bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| license: other | |
| license_name: deepseek-license | |
| license_link: LICENSE | |
| base_model: deepseek-ai/DeepSeek-Coder-V2-Instruct | |
| tags: | |
| - mlx | |
| # nafisabdkhan/DeepSeek-Coder-V2-Instruct-mlx-2Bit | |
| The Model [nafisabdkhan/DeepSeek-Coder-V2-Instruct-mlx-2Bit](https://huggingface.co/nafisabdkhan/DeepSeek-Coder-V2-Instruct-mlx-2Bit) was converted to MLX format from [deepseek-ai/DeepSeek-Coder-V2-Instruct](https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Instruct) using mlx-lm version **0.22.3**. | |
| ## Use with mlx | |
| ```bash | |
| pip install mlx-lm | |
| ``` | |
| ```python | |
| from mlx_lm import load, generate | |
| model, tokenizer = load("nafisabdkhan/DeepSeek-Coder-V2-Instruct-mlx-2Bit") | |
| prompt="hello" | |
| if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None: | |
| messages = [{"role": "user", "content": prompt}] | |
| prompt = tokenizer.apply_chat_template( | |
| messages, tokenize=False, add_generation_prompt=True | |
| ) | |
| response = generate(model, tokenizer, prompt=prompt, verbose=True) | |
| ``` | |