Instructions to use rinna/youri-7b-chat-gptq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rinna/youri-7b-chat-gptq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="rinna/youri-7b-chat-gptq")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("rinna/youri-7b-chat-gptq") model = AutoModelForCausalLM.from_pretrained("rinna/youri-7b-chat-gptq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use rinna/youri-7b-chat-gptq with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rinna/youri-7b-chat-gptq" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rinna/youri-7b-chat-gptq", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/rinna/youri-7b-chat-gptq
- SGLang
How to use rinna/youri-7b-chat-gptq with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "rinna/youri-7b-chat-gptq" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rinna/youri-7b-chat-gptq", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "rinna/youri-7b-chat-gptq" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rinna/youri-7b-chat-gptq", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use rinna/youri-7b-chat-gptq with Docker Model Runner:
docker model run hf.co/rinna/youri-7b-chat-gptq
Download quantize_config.json from rinna/youri-7b-chat-gptq: direct link, hf CLI and curl.
- Browser
- Download file 211 Bytes
-
https://huggingface.co/rinna/youri-7b-chat-gptq/resolve/main/quantize_config.json
- Command line
-
hf download hf://rinna/youri-7b-chat-gptq/quantize_config.json
-
curl -L -o quantize_config.json https://huggingface.co/rinna/youri-7b-chat-gptq/resolve/main/quantize_config.json
211 Bytes
| { | |
| "bits": 4, | |
| "group_size": 128, | |
| "damp_percent": 0.01, | |
| "desc_act": false, | |
| "static_groups": false, | |
| "sym": true, | |
| "true_sequential": true, | |
| "model_name_or_path": null, | |
| "model_file_base_name": null | |
| } |