Instructions to use nzs234/siglip2-so400m-aesthetic-scorer-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nzs234/siglip2-so400m-aesthetic-scorer-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nzs234/siglip2-so400m-aesthetic-scorer-v1") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nzs234/siglip2-so400m-aesthetic-scorer-v1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "format": "aesthetic_local_standalone_v1", | |
| "source_checkpoint": "E:\\AI\\Tagger2_Inference\\models\\local_aesthetic_run1\\best_by_test_rmse.pt", | |
| "backbone_dir": "backbone", | |
| "head_file": "head.safetensors", | |
| "model": { | |
| "backbone_name": "google/siglip2-so400m-patch16-512", | |
| "hidden_dim": 2048, | |
| "dropout": 0.2, | |
| "full_finetune": false, | |
| "processor_use_fast": false | |
| }, | |
| "data": { | |
| "score_min": 1.0, | |
| "score_max": 9.0 | |
| } | |
| } |