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:
- 9b9db8e09e14c71cc7ae9c56a7ad3b36da8e01cf1ba3091d5f18160077b10317
- Size of remote file:
- 7.86 GB
- SHA256:
- ce4681170e7379e26455c0f891a0654c387834cc8675d16a2f6564e5c0124edd
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