Instructions to use pipenetwork/DeepSeek-V4.1-Flash-MLX-mixed-4_8bit-engram6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use pipenetwork/DeepSeek-V4.1-Flash-MLX-mixed-4_8bit-engram6 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("pipenetwork/DeepSeek-V4.1-Flash-MLX-mixed-4_8bit-engram6") 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 pipenetwork/DeepSeek-V4.1-Flash-MLX-mixed-4_8bit-engram6 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "pipenetwork/DeepSeek-V4.1-Flash-MLX-mixed-4_8bit-engram6" --prompt "Once upon a time"
- Atomic Chat
- Xet hash:
- 16eaf9eedc3d7d7fab594e4a7a048f2d81caf49a6b3ff69ca003cdc1ba284342
- Size of remote file:
- 7.86 GB
- SHA256:
- 2a4c7761b7381a9372b792b249d478be694f050373f40958410a27eb2fb1a22d
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