Instructions to use naver-ellm/HyperCLOVAX-SEED-Text-Instruct-0.5B-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use naver-ellm/HyperCLOVAX-SEED-Text-Instruct-0.5B-MLX 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("naver-ellm/HyperCLOVAX-SEED-Text-Instruct-0.5B-MLX") 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 naver-ellm/HyperCLOVAX-SEED-Text-Instruct-0.5B-MLX with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "naver-ellm/HyperCLOVAX-SEED-Text-Instruct-0.5B-MLX"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "naver-ellm/HyperCLOVAX-SEED-Text-Instruct-0.5B-MLX" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "naver-ellm/HyperCLOVAX-SEED-Text-Instruct-0.5B-MLX", "messages": [ {"role": "user", "content": "Hello"} ] }' - Atomic Chat
Download tokenizer.json from naver-ellm/HyperCLOVAX-SEED-Text-Instruct-0.5B-MLX: direct link, hf CLI and curl.
- Browser
- Download file 8.03 MB
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https://huggingface.co/naver-ellm/HyperCLOVAX-SEED-Text-Instruct-0.5B-MLX/resolve/main/tokenizer.json
- Command line
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hf download hf://naver-ellm/HyperCLOVAX-SEED-Text-Instruct-0.5B-MLX/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/naver-ellm/HyperCLOVAX-SEED-Text-Instruct-0.5B-MLX/resolve/main/tokenizer.json
8.03 MB
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