Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use platzi/platzi-vit-model-elyager with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use platzi/platzi-vit-model-elyager with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="platzi/platzi-vit-model-elyager") 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("platzi/platzi-vit-model-elyager") model = AutoModelForImageClassification.from_pretrained("platzi/platzi-vit-model-elyager") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files
runs/Jan13_09-29-27_e41a5f5355d5/events.out.tfevents.1673603462.e41a5f5355d5.1186.2
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