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
File size: 307 Bytes
46801e9 fc8b3f4 6f9b866 46801e9 fc8b3f4 46801e9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"architectures": [
"ResNet50AffectiveFeatureExtractor"
],
"auto_map": {
"AutoConfig": "config.ResnetConfig",
"AutoModel": "model.ResNet50AffectiveFeatureExtractor"
},
"model_type": "ResNet50AffectiveFeatureExtractor",
"torch_dtype": "float32",
"transformers_version": "4.47.1"
}
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