Instructions to use Saads/bird_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Saads/bird_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Saads/bird_classification_model")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Saads/bird_classification_model") model = AutoModelForAudioClassification.from_pretrained("Saads/bird_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a57143e76d13b6d56a8f1e310df90d93616b7efddcc4708e258d7997ad06de5a
- Size of remote file:
- 3.52 kB
- SHA256:
- 292dfd4162ea2a36a89ac56cd424ee2296626558d7d89caf1211ca542d33e993
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.