Instructions to use pipenetwork/DeepSeek-V4-Flash-MLX-REAP37 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use pipenetwork/DeepSeek-V4-Flash-MLX-REAP37 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-Flash-MLX-REAP37") 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-Flash-MLX-REAP37 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-Flash-MLX-REAP37" --prompt "Once upon a time"
- Xet hash:
- 68b03142c5acc9d6aaf5518e0f84461c62a30448654610d516e70488a92314bf
- Size of remote file:
- 5.61 GB
- SHA256:
- 7bc11973ce618830eb6d230f4819dc0933d4df75019ef4d262ee30dd67fde4f0
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