Instructions to use mrtoots/unsloth-DeepSeek-V3.1-MLX-2Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrtoots/unsloth-DeepSeek-V3.1-MLX-2Bit with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mrtoots/unsloth-DeepSeek-V3.1-MLX-2Bit", dtype="auto") - MLX
How to use mrtoots/unsloth-DeepSeek-V3.1-MLX-2Bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir unsloth-DeepSeek-V3.1-MLX-2Bit mrtoots/unsloth-DeepSeek-V3.1-MLX-2Bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- Unsloth Studio new
How to use mrtoots/unsloth-DeepSeek-V3.1-MLX-2Bit with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for mrtoots/unsloth-DeepSeek-V3.1-MLX-2Bit to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for mrtoots/unsloth-DeepSeek-V3.1-MLX-2Bit to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mrtoots/unsloth-DeepSeek-V3.1-MLX-2Bit to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="mrtoots/unsloth-DeepSeek-V3.1-MLX-2Bit", max_seq_length=2048, )
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- 4.85 GB xet
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- 4.85 GB xet
- 4.77 GB xet
- 4.77 GB xet
- 4.85 GB xet
- 4.77 GB xet
- 4.77 GB xet
- 4.85 GB xet
- 4.77 GB xet
- 4.77 GB xet
- 4.85 GB xet
- 4.77 GB xet
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