Instructions to use hf-tiny-model-private/tiny-random-CvtForImageClassification 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-CvtForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-tiny-model-private/tiny-random-CvtForImageClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-CvtForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-tiny-model-private/tiny-random-CvtForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-CvtForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 5.16 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-CvtForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-CvtForImageClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-CvtForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
5.16 MB
- Xet hash:
- 61e29f5300dbca561ee848f42b4c826810a3bd966931ae5db8e95437cb99db31
- Size of remote file:
- 5.16 MB
- SHA256:
- a8beebd7b5e4ec2c2b8a64e12d4bc7cdeb672b240e8cbf12733ad0c47c0f5e16
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