Instructions to use apoth/bird_sounds_classification_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apoth/bird_sounds_classification_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="apoth/bird_sounds_classification_1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("apoth/bird_sounds_classification_1") model = AutoModelForAudioClassification.from_pretrained("apoth/bird_sounds_classification_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from apoth/bird_sounds_classification_1: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/apoth/bird_sounds_classification_1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://apoth/bird_sounds_classification_1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/apoth/bird_sounds_classification_1/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 72f2e2dab23954058db7a474420cf39d7c9563362582d169a091e8f99b67de04
- Size of remote file:
- 378 MB
- SHA256:
- 60730c46b2c48de6a1c313398f83d30fa1725fcb82921a676feb7e6c8069ad55
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