Instructions to use Dewa/dog_emotion_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dewa/dog_emotion_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Dewa/dog_emotion_v2") 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("Dewa/dog_emotion_v2") model = AutoModelForImageClassification.from_pretrained("Dewa/dog_emotion_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
language:
- en
metrics:
- accuracy
pipeline_tag: image-classification
Model Card for Model ID
This model is intended to detect emotion of a 🐕dog by its 📸image
Model Details
Model is fine-tunned using kaggle-dog-emotion-dataset It classify the dog's emotion into .😔sad,😀happy,😡angry,😌relaxed.
sometime machine can detect the feeling of our four leged buddy