Instructions to use hf-tiny-model-private/tiny-random-CvtModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-CvtModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-CvtModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-CvtModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-CvtModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-CvtModel: direct link, hf CLI and curl.
- Browser
- Download file 5.25 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-CvtModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-CvtModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-CvtModel/resolve/main/pytorch_model.bin
5.25 MB
- Xet hash:
- 46bd5dd4c14bab28a9142bb566bd807ef729db867a9fa7da5281cc193e80c8df
- Size of remote file:
- 5.25 MB
- SHA256:
- 41ec609fe8c4d191bc6e6408069f09fec8392753321204859b908267b79da9d6
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