Instructions to use rohithsiddhartha/DeepSeek-R1-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use rohithsiddhartha/DeepSeek-R1-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir DeepSeek-R1-4bit rohithsiddhartha/DeepSeek-R1-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
mlx-community/DeepSeek-R1-4bit
The Model mlx-community/DeepSeek-R1-4bit was converted to MLX format from deepseek-ai/DeepSeek-R1 using mlx-lm version 0.21.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/DeepSeek-R1-4bit")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
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Model tree for rohithsiddhartha/DeepSeek-R1-4bit
Base model
deepseek-ai/DeepSeek-R1