Image Classification
Transformers
PyTorch
TensorBoard
beit
Generated from Trainer
Eval Results (legacy)
Instructions to use ChasingMercer/beit-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChasingMercer/beit-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ChasingMercer/beit-base") 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("ChasingMercer/beit-base") model = AutoModelForImageClassification.from_pretrained("ChasingMercer/beit-base") - Notebooks
- Google Colab
- Kaggle
Commit ·
0d176a1
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Parent(s): 56385bf
Model save
Browse files
runs/Mar06_16-20-32_pop-os/events.out.tfevents.1678119648.pop-os.164622.12
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