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
| from transformers import PretrainedConfig | |
| class ResnetConfig(PretrainedConfig): | |
| model_type = "ResNet50AffectiveFeatureExtractor" | |
| def __init__( | |
| self, | |
| **kwargs, | |
| ): | |
| super().__init__(**kwargs) |