Instructions to use apoth/bird_sounds_classification_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apoth/bird_sounds_classification_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="apoth/bird_sounds_classification_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("apoth/bird_sounds_classification_2") model = AutoModelForAudioClassification.from_pretrained("apoth/bird_sounds_classification_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from apoth/bird_sounds_classification_2: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/apoth/bird_sounds_classification_2/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://apoth/bird_sounds_classification_2@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/apoth/bird_sounds_classification_2/resolve/refs%2Fpr%2F1/pytorch_model.bin
378 MB
- Xet hash:
- 0a5d06bf597ec60c693037e69a53b68b69b3c245738052465de0058ba739355a
- Size of remote file:
- 378 MB
- SHA256:
- 1f56e80762832fd3578f06072e9bbbc11561f5501ff936313359f7c712292a55
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