Update README.md

README.md

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 ConvNext trained on the XCL dataset from BirdSet, covering 9736 bird species from Xeno-Canto. Please refer to the [BirdSet Paper](https://arxiv.org/pdf/2403.10380) and the 
 [BirdSet Repository](https://github.com/DBD-research-group/BirdSet/tree/main) for further information. 
 
+### Model Details
+ConvNeXT is a pure convolutional model (ConvNet), inspired by the design of Vision Transformers, that claims to outperform them.
+
+## How to use
+The BirdSet data needs a custom processor that is available in the BirdSet repository. The model does not have a processor available. 
+The model accepts a mono image (spectrogram) as input (e.g., `torch.Size([16, 1, 128, 1024])`)
+
 - The model is trained on 5-second clips of bird vocalizations.
 - num_channels: 1
 - pretrained checkpoint: facebook/convnext-base-224-22k
@@ -17,14 +24,6 @@ ConvNext trained on the XCL dataset from BirdSet, covering 9736 bird species fro
 - melscale: n_mels: 128, n_stft: 513
 - dbscale: top_db: 80
 
-### Model Details
-ConvNeXT is a pure convolutional model (ConvNet), inspired by the design of Vision Transformers, that claims to outperform them.
-
-## How to use
-The BirdSet data needs a custom processor that is available in the BirdSet repository. The model does not have a processor available. 
-The model accepts a mono image (spectrogram) as input (e.g., `torch.Size([16, 1, 128, 1024])`)
-
-
 ```python
 import torch
 from transformers import AutoModelForImageClassification