Instructions to use beezu/Violet_Magcap-12B-MLX-3Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use beezu/Violet_Magcap-12B-MLX-3Bit 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("beezu/Violet_Magcap-12B-MLX-3Bit") 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 beezu/Violet_Magcap-12B-MLX-3Bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "beezu/Violet_Magcap-12B-MLX-3Bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "beezu/Violet_Magcap-12B-MLX-3Bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "beezu/Violet_Magcap-12B-MLX-3Bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
| {% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system | |
| You are a helpful assistant.<|im_end|> | |
| ' }}{% endif %}{{'<|im_start|>' + message['role'] + ' | |
| ' + message['content'] + '<|im_end|>' + ' | |
| '}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant | |
| ' }}{% endif %} |