Instructions to use anderloh/HuggingfaceTest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anderloh/HuggingfaceTest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anderloh/HuggingfaceTest")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anderloh/HuggingfaceTest") model = AutoModelForAudioClassification.from_pretrained("anderloh/HuggingfaceTest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Training in progress, epoch 17
Verified signatureb60bdd2 -
Training in progress, epoch 16
Verified signature3bd65db -
Training in progress, epoch 14
Verified signature9b33484 -
Training in progress, epoch 13
Verified signaturea731c5a -
Training in progress, epoch 12
Verified signatured30794c -
Training in progress, epoch 9
Verified signature64f8d28 -
Training in progress, epoch 8
Verified signature29c000a -
Training in progress, epoch 6
Verified signatureb50fdee -
Training in progress, epoch 5
Verified signaturea1c5efe -
Training in progress, epoch 4
Verified signature197a844 -
Training in progress, epoch 4
Verified signature1e59fb1 -
Training in progress, epoch 1
Verified signatureee77cf2 -
Training in progress, epoch 0
Verified signature2a042fd -
initial commit
Verified signaturec864196