Image Classification
Transformers
PyTorch
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use dennisjooo/emotion_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dennisjooo/emotion_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dennisjooo/emotion_classification") 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("dennisjooo/emotion_classification") model = AutoModelForImageClassification.from_pretrained("dennisjooo/emotion_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ccda1f5d879b118184e7f017a338feb8179ef903bed3ef526822f5232a42e02
- Size of remote file:
- 4.03 kB
- SHA256:
- 7d0a0ca31590e1bb9305f81f29252aace408bdc25efad7fc8ac010a9565b7cf2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.