Image Classification
Transformers
PyTorch
TensorBoard
English
beit
Generated from Trainer
Eval Results (legacy)
Instructions to use DunnBC22/dit-base-Document_Classification-RVL_CDIP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/dit-base-Document_Classification-RVL_CDIP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DunnBC22/dit-base-Document_Classification-RVL_CDIP") 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-Document_Classification-RVL_CDIP") model = AutoModelForImageClassification.from_pretrained("DunnBC22/dit-base-Document_Classification-RVL_CDIP") - Notebooks
- Google Colab
- Kaggle
File size: 167 Bytes
2828de2 | 1 2 3 4 5 6 7 | {
"epoch": 3.0,
"train_loss": 0.17273353269466987,
"train_runtime": 60970.1196,
"train_samples_per_second": 1.311,
"train_steps_per_second": 0.01
} |