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")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ChasingMercer/beit-base") model = AutoModelForImageClassification.from_pretrained("ChasingMercer/beit-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitignore from ChasingMercer/beit-base: direct link, hf CLI and curl.
- Browser
- Download file 13 Bytes
-
https://huggingface.co/ChasingMercer/beit-base/resolve/main/.gitignore
- Command line
-
hf download hf://ChasingMercer/beit-base/.gitignore
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curl -L -o .gitignore https://huggingface.co/ChasingMercer/beit-base/resolve/main/.gitignore
13 Bytes
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