Instructions to use fordb/bird2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fordb/bird2vec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="fordb/bird2vec")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("fordb/bird2vec") model = AutoModelForAudioClassification.from_pretrained("fordb/bird2vec", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from fordb/bird2vec: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/fordb/bird2vec/resolve/main/training_args.bin
- Command line
-
hf download hf://fordb/bird2vec/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/fordb/bird2vec/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- b25994d9bbe4717276858528e6942787217b2f8a7c88230f84c5967540992e77
- Size of remote file:
- 4.98 kB
- SHA256:
- d9a69b9d428a95deedef0cd066fb9f57eb513a00fa455a8560d03d0d904f4ec8
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