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README.md

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+---
+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)
+
+## Citation

model.safetensors

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