Instructions to use nguyenvulebinh/heyarmar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nguyenvulebinh/heyarmar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="nguyenvulebinh/heyarmar")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("nguyenvulebinh/heyarmar") model = AutoModelForAudioClassification.from_pretrained("nguyenvulebinh/heyarmar", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Create README.md
7a8d5af -
Upload feature extractor
40f5535 -
Upload WavLMForSequenceClassification
ec9c16d -
Upload feature extractor
7baef79 -
Upload WavLMForSequenceClassification
765502a -
Upload feature extractor
604b976 -
Upload WavLMForSequenceClassification
8089f44 -
Upload feature extractor
cd64134 -
Upload WavLMForSequenceClassification
00f4191 -
Upload feature extractor
29784e3 -
Upload WavLMForSequenceClassification
3631597 -
Upload feature extractor
80e7d3a -
Upload WavLMForSequenceClassification
3763828 -
Upload feature extractor
b232cb5 -
Upload WavLMForSequenceClassification
9f51588
-
Upload feature extractor
5436972 -
Upload WavLMForSequenceClassification
8c292db -
initial commit
bf14a97