Instructions to use Woleek/ResNet50AffectiveFeatureExtractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Woleek/ResNet50AffectiveFeatureExtractor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Woleek/ResNet50AffectiveFeatureExtractor", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Woleek/ResNet50AffectiveFeatureExtractor", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b3e14c3a788db2d76671c7d07e62e565aef5965c212e593cd9e33a01ee36ad3
- Size of remote file:
- 101 MB
- SHA256:
- 042169f2ec560953412d12f8aad4b164a10ad317c25f834244a83a1c3ec70da4
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