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README.md
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This model generate a short textual description of any audio file.
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```bash
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pip install conette
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```
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```py
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from conette import CoNeTTEConfig, CoNeTTEModel
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config = CoNeTTEConfig.from_pretrained("Labbeti/conette")
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model = CoNeTTEModel.from_pretrained("Labbeti/conette", config=config)
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```
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It was created by [@Labbeti](https://hf.co/Labbeti).
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This model generate a short textual description of any audio file.
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## Installation
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```bash
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pip install conette
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```
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## Usage
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```py
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from conette import CoNeTTEConfig, CoNeTTEModel
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config = CoNeTTEConfig.from_pretrained("Labbeti/conette")
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model = CoNeTTEModel.from_pretrained("Labbeti/conette", config=config)
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path = "/my/path/to/audio.wav"
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outputs = model(path)
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cands = outputs["cands"][0]
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print(cands)
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```
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## Performance
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TODO
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## Additional information
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The encoder part of the architecture is based on a ConvNeXt model for audio classification, available here: https://huggingface.co/topel/ConvNeXt-Tiny-AT.
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The encoder weights used are named "convnext_tiny_465mAP_BL_AC_70kit.pth", available on Zenodo: https://zenodo.org/record/8020843.
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It was created by [@Labbeti](https://hf.co/Labbeti).
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