Instructions to use batmac/Phi-3-mini-128k-instruct-mlx-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use batmac/Phi-3-mini-128k-instruct-mlx-8bit 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("batmac/Phi-3-mini-128k-instruct-mlx-8bit") 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 batmac/Phi-3-mini-128k-instruct-mlx-8bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "batmac/Phi-3-mini-128k-instruct-mlx-8bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "batmac/Phi-3-mini-128k-instruct-mlx-8bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "batmac/Phi-3-mini-128k-instruct-mlx-8bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
- Xet hash:
- 0917f7db46cda0b63c5e8514b7252f1c4ae18937c51c2b09a7b69d0aa8c389f0
- Size of remote file:
- 4.06 GB
- SHA256:
- 6d02945d30694c4967a2df3ba9e1f3620808be6a3535c452428293a389b0867d
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