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:
- 804bfd4ea66554fe63f1c435c75c41bf9cdf169eb94e5319f181a97aedd129bc
- Size of remote file:
- 7.86 GB
- SHA256:
- 99dcd0517926919b9b3caa1d0d8734eb281a1e6af3f1c38be87f5c8289af7680
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