Instructions to use LoneStriker/Orca-2-13b-6.0bpw-h6-exl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LoneStriker/Orca-2-13b-6.0bpw-h6-exl2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="LoneStriker/Orca-2-13b-6.0bpw-h6-exl2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("LoneStriker/Orca-2-13b-6.0bpw-h6-exl2") model = AutoModelForCausalLM.from_pretrained("LoneStriker/Orca-2-13b-6.0bpw-h6-exl2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use LoneStriker/Orca-2-13b-6.0bpw-h6-exl2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LoneStriker/Orca-2-13b-6.0bpw-h6-exl2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LoneStriker/Orca-2-13b-6.0bpw-h6-exl2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/LoneStriker/Orca-2-13b-6.0bpw-h6-exl2
- SGLang
How to use LoneStriker/Orca-2-13b-6.0bpw-h6-exl2 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 "LoneStriker/Orca-2-13b-6.0bpw-h6-exl2" \ --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": "LoneStriker/Orca-2-13b-6.0bpw-h6-exl2", "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 "LoneStriker/Orca-2-13b-6.0bpw-h6-exl2" \ --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": "LoneStriker/Orca-2-13b-6.0bpw-h6-exl2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use LoneStriker/Orca-2-13b-6.0bpw-h6-exl2 with Docker Model Runner:
docker model run hf.co/LoneStriker/Orca-2-13b-6.0bpw-h6-exl2
| url: https://huggingface.co/microsoft/Orca-2-13b | |
| branch: main | |
| download date: 2023-11-20 21:44:37 | |
| sha256sum: | |
| 48b50d9d6ef77522b210c62ec214dd01295fcf88a3160acce32cae23d033ce1d pytorch_model-00001-of-00006.bin | |
| d5dec51a499eea69793a89ce4409b019092829a8efbe5ca0f73cd1da3b7431d3 pytorch_model-00002-of-00006.bin | |
| 5bd111371970c260e3b38685f6a39bc54ba189e9aa1297e142b9193e21fab415 pytorch_model-00003-of-00006.bin | |
| 9870c5705b3b409ba7ee8c60c6e785c350d8f69194ea58db11a8acfef808a4cf pytorch_model-00004-of-00006.bin | |
| e17d513a94757fed6a86e48d9f425fcf0a52f8bc47b83f84e809eabc5e685196 pytorch_model-00005-of-00006.bin | |
| 974119123f7033984e573b0d2c9754275bd448c688a09488e52f2f44206785e1 pytorch_model-00006-of-00006.bin | |
| 9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347 tokenizer.model | |