Instructions to use apoth/bird_sounds_classification_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apoth/bird_sounds_classification_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="apoth/bird_sounds_classification_3")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("apoth/bird_sounds_classification_3") model = AutoModelForAudioClassification.from_pretrained("apoth/bird_sounds_classification_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from apoth/bird_sounds_classification_3: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/apoth/bird_sounds_classification_3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://apoth/bird_sounds_classification_3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/apoth/bird_sounds_classification_3/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 6f8ebf84249635a85715e6105652f2577796b2af7fccf3d464b2557c7a45c69d
- Size of remote file:
- 378 MB
- SHA256:
- bfba778481eab31fb88ab6347a75621d07f6fd70a1dc923254bd666468ee3ee4
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