{"library":"optimum-onnx","type":"library","category":null,"description":"Optimum ONNX is a specialized extension of the Hugging Face Optimum library, providing a streamlined interface for exporting Hugging Face Transformer models (and other architectures like Diffusers, Timm, Sentence Transformers) to the ONNX format. It facilitates efficient inference and deployment using ONNX Runtime, including features like graph optimization and quantization. Currently at version 0.1.0, it sees regular updates to support new Hugging Face models and ensure compatibility with underlying libraries like PyTorch and Transformers.","language":"python","status":"active","version":"0.1.0","tags":["huggingface","onnx","onnxruntime","transformers","machine-learning","inference","deep-learning","optimization"],"install":[{"cmd":"pip install optimum-onnx","imports":["from optimum.onnxruntime import ORTModelForSequenceClassification"]},{"cmd":"pip install \"optimum-onnx[onnxruntime]\"","imports":[]},{"cmd":"pip install \"optimum-onnx[onnxruntime-gpu]\"","imports":[]}],"homepage":null,"github":"https://github.com/huggingface/optimum-onnx","docs":null,"changelog":null,"pypi":"https://pypi.org/project/optimum-onnx/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":40,"avg_install_s":82.5,"avg_import_s":17.07,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/optimum-onnx/compatibility"},"provenance":{"verified_status":"import_fail","verified_at":"Fri Jul 03","last_verified":"Fri Jul 03","next_check":"Fri Jul 10","install_tag":null}}