Instructions to use BlairQ/OCRonos-Q4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use BlairQ/OCRonos-Q4 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("BlairQ/OCRonos-Q4") 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 BlairQ/OCRonos-Q4 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "BlairQ/OCRonos-Q4"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "BlairQ/OCRonos-Q4" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "BlairQ/OCRonos-Q4", "messages": [ {"role": "user", "content": "Hello"} ] }' - Atomic Chat
Download generation_config.json from BlairQ/OCRonos-Q4: direct link, hf CLI and curl.
- Browser
- Download file 126 Bytes
-
https://huggingface.co/BlairQ/OCRonos-Q4/resolve/73fbbf3f71d3f53b77c0589b8c14f1994d9a424b/generation_config.json
- Command line
-
hf download hf://BlairQ/OCRonos-Q4@73fbbf3f71d3f53b77c0589b8c14f1994d9a424b/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/BlairQ/OCRonos-Q4/resolve/73fbbf3f71d3f53b77c0589b8c14f1994d9a424b/generation_config.json
126 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 128000, | |
| "eos_token_id": 128001, | |
| "transformers_version": "4.38.0.dev0" | |
| } | |