Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use JuandaBula/vit-model-juan-bula with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JuandaBula/vit-model-juan-bula with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="JuandaBula/vit-model-juan-bula") 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("JuandaBula/vit-model-juan-bula") model = AutoModelForImageClassification.from_pretrained("JuandaBula/vit-model-juan-bula", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4114257f7daa5a62bc9e22d8785c0aa86bec8024e3f0a10ec350660a05cfbb81
- Size of remote file:
- 343 MB
- SHA256:
- e617c790c2b5a74d227dbc8e7158ce9daff15ee24dcc03fcc399b7074f4cb9d5
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