Instructions to use Bur3hani/Machi-Know-DeepSeek-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Bur3hani/Machi-Know-DeepSeek-8B with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("Bur3hani/Machi-Know-DeepSeek-8B") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use Bur3hani/Machi-Know-DeepSeek-8B with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "Bur3hani/Machi-Know-DeepSeek-8B"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "Bur3hani/Machi-Know-DeepSeek-8B" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Bur3hani/Machi-Know-DeepSeek-8B", "messages": [ {"role": "user", "content": "Hello"} ] }' - Atomic Chat
- Xet hash:
- 4131680c58afa15f9486ed7d99c9ec7a842e144bf15542fb91369bbae6178bb9
- Size of remote file:
- 17.2 MB
- SHA256:
- 7910d2be31cd1d69918b7a2d9e9b33c62c392d810c01768744426d9ac4677b6f
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