Feature Extraction
Transformers
Safetensors
English
usad2
automatic-speech-recognition
audio-classification
audio
speech
music
custom_code
Instructions to use MIT-SLS/USAD2-Small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MIT-SLS/USAD2-Small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="MIT-SLS/USAD2-Small", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MIT-SLS/USAD2-Small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
94d3a9f | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:28a4e9c6b52ad27ccba372041c6e3565312bb6bf2d79ceb0ee943c96e78221d5
size 99074696
|