Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use MaxP/vit-base-riego with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MaxP/vit-base-riego with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MaxP/vit-base-riego") 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("MaxP/vit-base-riego") model = AutoModelForImageClassification.from_pretrained("MaxP/vit-base-riego") - Notebooks
- Google Colab
- Kaggle
Commit ·
8ede0d6
1
Parent(s): 52ec8bb
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (ff3e8775de87b0923c9ffaad800b5a5e8e4bb8b3)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9d03bf5e1e649d6e78a5330db9a99071a5d0cd302d84d7ac3cf317f7ceeac018
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size 343223972
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