Instructions to use shivarama23/DiT_image_quality with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shivarama23/DiT_image_quality with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="shivarama23/DiT_image_quality") 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("shivarama23/DiT_image_quality") model = AutoModelForImageClassification.from_pretrained("shivarama23/DiT_image_quality", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29d247ed432e309fbe80886359fff736a3938e035cf275a546e77a0e83638976
- Size of remote file:
- 343 MB
- SHA256:
- 5926de440f41d44dff1e56de91ec9c663914e646fc2704a92f53d746812cd943
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