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resnet-dogcat
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更新 README.md

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@ -53,6 +53,14 @@ predicted_label = logits.argmax(-1).item()
print(model.config.id2label[predicted_label])
```
```python
import gradio as gr
pipe = pipeline("image-classification", model="ailab/resnet-dogcat")
gr.Interface.from_pipeline(pipe).launch(server_name="0.0.0.0")
```
![1716790696165.png](https://img2.imgtp.com/2024/05/27/hIlNpCRj.png)
## Conclusion
This repository provides a comprehensive solution for training and performing inference on a Cat-Dog classification task using a ResNet-50 model. The training script demonstrates how to preprocess data, train the model, and save the trained model. The inference script shows how to use the trained model to classify new images.