Instructions to use ideepankarsharma2003/AI_ImageClassification_SDXL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ideepankarsharma2003/AI_ImageClassification_SDXL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ideepankarsharma2003/AI_ImageClassification_SDXL") 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("ideepankarsharma2003/AI_ImageClassification_SDXL") model = AutoModelForImageClassification.from_pretrained("ideepankarsharma2003/AI_ImageClassification_SDXL") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc1410e743b6a0ef16df161f4089c9250eafe6b1a856b0381d5a87ba07e779d8
- Size of remote file:
- 4.73 kB
- SHA256:
- 9edbd48f74807283cdb5f5493284bc0a2de08fc9ebd74b0ba5b2bb1b9391dc70
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.