Update README.md

README.md

@@ -1,39 +1,26 @@
----
-library_name: transformers
-tags: []
----
-
-# ConvNext (trained on XCL from BirdSet)
-
-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
-- sampling_rate: 32_000
-- normalize spectrogram: mean: -4.268, std: 4.569 (from esc-50)
-- spectrogram: n_fft: 1024, hop_length: 320, power: 2.0
-- melscale: n_mels: 128, n_stft: 513
-- dbscale: top_db: 80
-
-```python
-import torch
-from transformers import AutoModelForImageClassification
-from datasets import load_dataset
-
-dataset = load_dataset("DBD-research-group/BirdSet", "HSN")
-```
-
-## Model Source
-- **Repository:** [BirdSet Repository](https://github.com/DBD-research-group/BirdSet/tree/main)
-- **Paper [optional]:** [BirdSet Paper](https://arxiv.org/pdf/2403.10380)
-
+---
+library_name: transformers
+tags: []
+---
+
+# ConvNext (trained on XCL from BirdSet)
+
+ConvNext trained on the XCL dataset from BirdSet, covering 9736 bird species from Xeno-Canto.
+
+### 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
+- sampling_rate: 32_000
+- normalize spectrogram: mean: -4.268, std: 4.569 (from esc-50)
+- spectrogram: n_fft: 1024, hop_length: 320, power: 2.0
+- melscale: n_mels: 128, n_stft: 513
+- dbscale: top_db: 80
+
 ## Citation