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:
- a3b84f6ee4138b515c0edd0b638eb2fc83707c4db2161bf1c8f09ca579e0c02c
- Size of remote file:
- 3.31 kB
- SHA256:
- e6052740dd844b8ddcc65e37222209ee1a6f4664a893539d11a0080dd8d82229
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