Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use poolrf2001/platzi-vit-model-pool-river with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use poolrf2001/platzi-vit-model-pool-river with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="poolrf2001/platzi-vit-model-pool-river") 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("poolrf2001/platzi-vit-model-pool-river") model = AutoModelForImageClassification.from_pretrained("poolrf2001/platzi-vit-model-pool-river") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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oid sha256:a2a8c108955be4dc324cada6d0c3a123099a7e24ab67deb987583266f43dfdc3
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size 343227052
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