Instructions to use Open-Orca/OpenOrca with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Open-Orca/OpenOrca with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Open-Orca/OpenOrca")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Open-Orca/OpenOrca") model = AutoModelForCausalLM.from_pretrained("Open-Orca/OpenOrca", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Open-Orca/OpenOrca with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Open-Orca/OpenOrca" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Open-Orca/OpenOrca", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Open-Orca/OpenOrca
- SGLang
How to use Open-Orca/OpenOrca 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 "Open-Orca/OpenOrca" \ --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": "Open-Orca/OpenOrca", "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 "Open-Orca/OpenOrca" \ --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": "Open-Orca/OpenOrca", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Open-Orca/OpenOrca with Docker Model Runner:
docker model run hf.co/Open-Orca/OpenOrca
Download pytorch_model-00002-of-00003.bin from Open-Orca/OpenOrca: direct link, hf CLI and curl.
- Browser
- Download file 9.9 GB
-
https://huggingface.co/Open-Orca/OpenOrca/resolve/main/pytorch_model-00002-of-00003.bin
- Command line
-
hf download hf://Open-Orca/OpenOrca/pytorch_model-00002-of-00003.bin
-
curl -L -o pytorch_model-00002-of-00003.bin https://huggingface.co/Open-Orca/OpenOrca/resolve/main/pytorch_model-00002-of-00003.bin
9.9 GB
- Xet hash:
- 61b24ef5cc844a42081c845ba59bdf70d5b9acba81545df6f82495a2ec3fc848
- Size of remote file:
- 9.9 GB
- SHA256:
- 69e0df73c5382f56d202f715b2f5f76d99709bf106c78e987fa01d03799a175c
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