Instructions to use Muinez/artwork-scorer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Muinez/artwork-scorer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Muinez/artwork-scorer") 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("Muinez/artwork-scorer") model = AutoModelForImageClassification.from_pretrained("Muinez/artwork-scorer") - Notebooks
- Google Colab
- Kaggle
Trained on 120,000 images collected from Pixiv rankings, the score is the normalized ratio of likes to views
This model is a fine-tuned version of facebook/convnextv2-base-22k-384
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Model tree for Muinez/artwork-scorer
Base model
facebook/convnextv2-base-22k-384