How to use from the
Use from the
Transformers library
# 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")
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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

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Model size
85.8M params
Tensor type
F32
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