Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Marxulia/emotion_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Marxulia/emotion_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Marxulia/emotion_classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Marxulia/emotion_classification") model = AutoModelForImageClassification.from_pretrained("Marxulia/emotion_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
9eb8eff | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:eaeb03e12e6764a699f4fa14a77f5f20ee278796fac37333f825944baf2de984
size 4600
|