Instructions to use thinkingface/test-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thinkingface/test-onnx with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("thinkingface/test-onnx") model = AutoModel.from_pretrained("thinkingface/test-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_quantized.onnx from thinkingface/test-onnx: direct link, hf CLI and curl.
- Browser
- Download file 110 MB
-
https://huggingface.co/thinkingface/test-onnx/resolve/main/model_quantized.onnx
- Command line
-
hf download hf://thinkingface/test-onnx/model_quantized.onnx
-
curl -L -o model_quantized.onnx https://huggingface.co/thinkingface/test-onnx/resolve/main/model_quantized.onnx
110 MB
- Xet hash:
- 783ba525c593dc957eeeb7b5f24e7f4a4557dad6c11d88cfc70c23a8fe7fccdc
- Size of remote file:
- 110 MB
- SHA256:
- ab71e6ebf4f105406fdd2e08d0e91f751ba51a5e38966dfc253d7053f4c8cc0a
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