Instructions to use sjug/DeepSeek-V3.2-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use sjug/DeepSeek-V3.2-MLX-4bit with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("sjug/DeepSeek-V3.2-MLX-4bit") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use sjug/DeepSeek-V3.2-MLX-4bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "sjug/DeepSeek-V3.2-MLX-4bit" --prompt "Once upon a time"
- Xet hash:
- 9b52a36c72ec477515c3cb2cad6bc7d7c7fd541b1832ea51f3dcfe076d25357d
- Size of remote file:
- 4.37 GB
- SHA256:
- 6c5a45902f6e619444b0ac1846fa30ac2717ca4d36e5abc1169f275b5f9a30da
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