Image Classification
Transformers
Safetensors
vit
deep-fake
ViT
detection
Image
transformers-4.49.0.dev0
precision-92.12
v2
Instructions to use AIImage12345/AI_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AIImage12345/AI_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="AIImage12345/AI_model") 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("AIImage12345/AI_model") model = AutoModelForImageClassification.from_pretrained("AIImage12345/AI_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a927f529ca006660900f1a51397b4aefa4f11a91bf35c91b66632bd7b6971ae0
- Size of remote file:
- 343 MB
- SHA256:
- 88ac0939285009e3700cfc9b9a0912b14b092d200ef0df86efe4f2cf190ea4de
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