Instructions to use venuv62/autotrained_spoof_detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use venuv62/autotrained_spoof_detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="venuv62/autotrained_spoof_detector") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("venuv62/autotrained_spoof_detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from venuv62/autotrained_spoof_detector: direct link, hf CLI and curl.
- Browser
- Download file 240 Bytes
-
https://huggingface.co/venuv62/autotrained_spoof_detector/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://venuv62/autotrained_spoof_detector/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/venuv62/autotrained_spoof_detector/resolve/main/preprocessor_config.json
240 Bytes
- Xet hash:
- 0bf9083f09ef515a0e3552b9787af958e8388c8bb279cd47e01d1647dfc8d30f
- Size of remote file:
- 240 Bytes
- SHA256:
- 63ae741f85ba4dfcb1917ef808968baaad3a395dd8067e970c872d0e6ac05f3b
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