Image Classification
Transformers
PyTorch
TensorBoard
beit
Generated from Trainer
Eval Results (legacy)
Instructions to use venuv62/beit-base-patch16-224-pt22k-ft22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use venuv62/beit-base-patch16-224-pt22k-ft22k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="venuv62/beit-base-patch16-224-pt22k-ft22k") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("venuv62/beit-base-patch16-224-pt22k-ft22k") model = AutoModelForImageClassification.from_pretrained("venuv62/beit-base-patch16-224-pt22k-ft22k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from venuv62/beit-base-patch16-224-pt22k-ft22k: direct link, hf CLI and curl.
- Browser
- Download file 347 MB
-
https://huggingface.co/venuv62/beit-base-patch16-224-pt22k-ft22k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://venuv62/beit-base-patch16-224-pt22k-ft22k/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/venuv62/beit-base-patch16-224-pt22k-ft22k/resolve/main/pytorch_model.bin
347 MB
- Xet hash:
- c6b5e2fa16011785c1dfa5da4b042f51b39dd31f81343ebc8f42b9dba4c9bb8c
- Size of remote file:
- 347 MB
- SHA256:
- d8292c68289c2856058aa0e7a73d19d2c7acd76ee5cf16dae3a132a0bd9a91f2
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