Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use SoulPerforms/visual_emotion_classification_vit_base_finetunned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SoulPerforms/visual_emotion_classification_vit_base_finetunned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SoulPerforms/visual_emotion_classification_vit_base_finetunned") 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("SoulPerforms/visual_emotion_classification_vit_base_finetunned") model = AutoModelForImageClassification.from_pretrained("SoulPerforms/visual_emotion_classification_vit_base_finetunned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9abfc480847a3a6f6589c68d789d70d94eee6bae7080128c75dc7daaa8fa8567
- Size of remote file:
- 4.66 kB
- SHA256:
- 7061a4691318b22a03af46800304f5f9b0f42c9a6403abcd65edc5826365c627
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