Text Generation
MLX
Safetensors
hunyuan_v1_dense
mlx-my-repo
hunyuan
translation
conversational
4-bit precision
Instructions to use illitan/Hy-MT2-1.8B-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use illitan/Hy-MT2-1.8B-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("illitan/Hy-MT2-1.8B-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
- LM Studio
- MLX LM
How to use illitan/Hy-MT2-1.8B-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 "illitan/Hy-MT2-1.8B-4bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "illitan/Hy-MT2-1.8B-4bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "illitan/Hy-MT2-1.8B-4bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
File size: 221 Bytes
198be17 | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"bos_token_id": 120000,
"do_sample": true,
"eos_token_id": 120020,
"pad_token_id": 120002,
"repetition_penalty": 1.05,
"temperature": 0.7,
"top_k": 20,
"top_p": 0.8,
"transformers_version": "4.57.6"
}
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