Instructions to use tcvrishank/histo_train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tcvrishank/histo_train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="tcvrishank/histo_train") 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("tcvrishank/histo_train") model = AutoModelForImageClassification.from_pretrained("tcvrishank/histo_train", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
update model card README.md
9f655d7 -
Model save
79d96c7 -
Model save
40af27d -
update model card README.md
f94e399 -
Model save
da09236 -
initial commit
5996e99