Image Classification
Transformers
PyTorch
TensorBoard
English
beit
Generated from Trainer
Eval Results (legacy)
Instructions to use DunnBC22/dit-base-Business_Documents_Classified_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/dit-base-Business_Documents_Classified_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DunnBC22/dit-base-Business_Documents_Classified_v2") 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("DunnBC22/dit-base-Business_Documents_Classified_v2") model = AutoModelForImageClassification.from_pretrained("DunnBC22/dit-base-Business_Documents_Classified_v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1d95a60927c9754c8bf83aa01c98873879ea3110b2193f52a0762048bfdada1
- Size of remote file:
- 343 MB
- SHA256:
- bc824bb0d36137b5c22c77d25c7a7e690020f2bae133543319e97af84df82ce4
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