Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use eormeno12/platzi_vit_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eormeno12/platzi_vit_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="eormeno12/platzi_vit_model") 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("eormeno12/platzi_vit_model") model = AutoModelForImageClassification.from_pretrained("eormeno12/platzi_vit_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46ae92f233f3e9985497103741ef62a0326c4aa149070a81d0a434df47962d08
- Size of remote file:
- 3.45 kB
- SHA256:
- fa8597e7a967378d264f92c1a40b587d69335bb3ea937940734f6dc404dc0d1a
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