Add Colab link

README.md

@@ -13,7 +13,7 @@ ConvNeXT is a pure convolutional model (ConvNet), inspired by the design of Visi
 
 ## 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, 343])`)
+The model accepts a mono image (spectrogram) as input (e.g., `torch.Size([16, 1, 128, 334])`)
 
 - The model is trained on 5-second clips of bird vocalizations.
 - num_channels: 1
@@ -24,7 +24,8 @@ The model accepts a mono image (spectrogram) as input (e.g., `torch.Size([16, 1,
 - melscale: n_mels: 128, n_stft: 513
 - dbscale: top_db: 80
 
-See [example inference notebook](https://github.com/DBD-research-group/BirdSet/blob/main/notebooks/tutorials/model_inference.ipynb):
+See [example inference notebook](https://github.com/DBD-research-group/BirdSet/blob/main/notebooks/tutorials/model_inference.ipynb).
+Run in [Google Colab](https://colab.research.google.com/drive/1pp_RCJEjSR4gPBGFtxDdgnr4Uk1_KimU?usp=sharing):
 
 ```python
 from transformers import ConvNextForImageClassification