Instructions to use tapadipti/tds-huggingpics with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tapadipti/tds-huggingpics with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="tapadipti/tds-huggingpics") 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("tapadipti/tds-huggingpics") model = AutoModelForImageClassification.from_pretrained("tapadipti/tds-huggingpics") - Notebooks
- Google Colab
- Kaggle
tds-huggingpics
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
Example Images
bed
chair
closet
couch
table
- Downloads last month
- 4
Evaluation results
- Accuracyself-reported0.875




