Instructions to use NEXTAltair/cache_aestheic-shadow-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NEXTAltair/cache_aestheic-shadow-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="NEXTAltair/cache_aestheic-shadow-v2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("NEXTAltair/cache_aestheic-shadow-v2") model = AutoModelForImageClassification.from_pretrained("NEXTAltair/cache_aestheic-shadow-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 369 Bytes
82df4bc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.65463551,
0.60715182,
0.61108185
],
"image_processor_type": "ViTImageProcessor",
"image_std": [
0.32903292,
0.32726001,
0.31909652
],
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 1024,
"width": 1024
}
}
|