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README.md
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- **Model type:** Vision transformer
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- **License:** MIT
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- **Finetuned from model:**
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## How to Get Started with the Model
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Example usage:
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from transformers import AutoImageProcessor, AutoModelForImageClassification, pipeline
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pipe = pipeline("image-classification", model="HardlyHumans/Facial-expression-detection")
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logits = outputs.logits
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predicted_class_idx = logits.argmax(-1).item()
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predicted_label = labels[predicted_class_idx]
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The net estimated CO2 emission using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) scale is around 8.82kg of CO2.
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- **Hardware Type:** T4
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- **Hours used:** 8+27
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- **Cloud Provider:** Google collabotary service
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## How to Get Started with the Model
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Example usage:
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```python
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from transformers import AutoImageProcessor, AutoModelForImageClassification, pipeline
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pipe = pipeline("image-classification", model="HardlyHumans/Facial-expression-detection")
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logits = outputs.logits
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predicted_class_idx = logits.argmax(-1).item()
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predicted_label = labels[predicted_class_idx]
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```
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The net estimated CO2 emission using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) scale is around 8.82kg of CO2.
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- **Developed by:** Hardly Humans club, IIT Dharwad
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- **Model type:** Vision transformer
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- **License:** MIT
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- **Finetuned from model:** google/vit-base-patch16-224-in21k
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- **Hardware Type:** T4
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- **Hours used:** 8+27
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- **Cloud Provider:** Google collabotary service
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