Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use AlCyede/emotion-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlCyede/emotion-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="AlCyede/emotion-classifier") 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("AlCyede/emotion-classifier") model = AutoModelForImageClassification.from_pretrained("AlCyede/emotion-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf36f02cf9488e7500223f2da25279d3c2a206ad01f61ac9c55b0691260addc3
- Size of remote file:
- 343 MB
- SHA256:
- fb080cacbbbcbb02b0ef074220c770c1d095f9c4748ebd359bade5c269c571b3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.