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:
- e1c6653ef98d26eefdd8e437102d940dc717b8912aa4f6aeaed79e30890d9283
- Size of remote file:
- 343 MB
- SHA256:
- 06045ed4a84add4f4c6d3ec322322238f1ac5a5948192602810a9be59783198a
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