Instructions to use DBD-research-group/Bird-MAE-Huge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DBD-research-group/Bird-MAE-Huge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="DBD-research-group/Bird-MAE-Huge", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DBD-research-group/Bird-MAE-Huge", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69905173301f68822fdcb8884844cf7459b9f0eeedea76c758d198a4f92d63cf
- Size of remote file:
- 2.52 GB
- SHA256:
- b6cfd0fc7d54e1e972911033a03af62ceef7b666a78273d18ff793fd33295c7f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.