Instructions to use GusLovesMath/LlaMATH-3-8B-Instruct-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use GusLovesMath/LlaMATH-3-8B-Instruct-4bit 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("GusLovesMath/LlaMATH-3-8B-Instruct-4bit") 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 GusLovesMath/LlaMATH-3-8B-Instruct-4bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "GusLovesMath/LlaMATH-3-8B-Instruct-4bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "GusLovesMath/LlaMATH-3-8B-Instruct-4bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GusLovesMath/LlaMATH-3-8B-Instruct-4bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
Upload folder using huggingface_hub (#3)
Browse files- 6b3c0da8bca263b5748491f9ffdfc758fc7841025215a569b247c5d2e6717da0 (45859a001fd1d1fccbe2ce2ac3ef03d7bb74f55a)
- 81f2f174c42329caec21a89b1e86547c728af45831e60194e82c71ab6645c235 (5669bd6a86c0eb40e02a531d37fa5b9b1d002b72)
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