Instructions to use sooks/idbwtiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sooks/idbwtiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sooks/idbwtiny") 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("sooks/idbwtiny") model = AutoModelForImageClassification.from_pretrained("sooks/idbwtiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a33ae28df5c874ef46073d9abad1581a1975e41597455074b7febba2605ac55
- Size of remote file:
- 4.86 kB
- SHA256:
- bda0c07890290c289875eb801caaf7e88e9c42f2d3de9ef6628b2f4027bd7545
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.