Image Classification
Transformers
PyTorch
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use RaymundoSGlz/vit_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RaymundoSGlz/vit_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="RaymundoSGlz/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("RaymundoSGlz/vit_model") model = AutoModelForImageClassification.from_pretrained("RaymundoSGlz/vit_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea86f66993a76edde212372d9a6d2257d9c235f68b5f8b480da9cfea9aa97a90
- Size of remote file:
- 3.9 kB
- SHA256:
- fe56e5013f863e73d13922d88e02cd60404f0584927c4c33edd8bd7d6bd7130e
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