Instructions to use pipenetwork/DeepSeek-V4-Flash-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use pipenetwork/DeepSeek-V4-Flash-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("pipenetwork/DeepSeek-V4-Flash-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 pipenetwork/DeepSeek-V4-Flash-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 "pipenetwork/DeepSeek-V4-Flash-MLX-4bit" --prompt "Once upon a time"
Ctrl+K
- deepseek_v4_mlx
- encoding
- 1.52 kB
- 7.19 kB
- 1.93 kB
- 170 Bytes
- 5.39 GB xet
- 6.19 GB xet
- 5.11 GB xet
- 6.17 GB xet
- 5.11 GB xet
- 6.19 GB xet
- 5.11 GB xet
- 6.17 GB xet
- 5.11 GB xet
- 6.19 GB xet
- 5.11 GB xet
- 6.17 GB xet
- 5.11 GB xet
- 6.19 GB xet
- 5.11 GB xet
- 6.17 GB xet
- 5.11 GB xet
- 6.19 GB xet
- 5.11 GB xet
- 6.17 GB xet
- 5.11 GB xet
- 6.19 GB xet
- 5.11 GB xet
- 6.17 GB xet
- 5.11 GB xet
- 6.19 GB xet
- 5.11 GB xet
- 6.17 GB xet
- 4.07 GB xet
- 177 kB
- 6.37 MB
- 801 Bytes