Automatic Speech Recognition
Transformers
Safetensors
lite-whisper
feature-extraction
audio
whisper
hf-asr-leaderboard
custom_code
Instructions to use efficient-speech/lite-whisper-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use efficient-speech/lite-whisper-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="efficient-speech/lite-whisper-small", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("efficient-speech/lite-whisper-small", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Improve model card with abstract and sample usage
#1
by nielsr HF Staff - opened
This PR enhances the model card by:
- Adding the full abstract of the paper, providing a more comprehensive overview of the LiteASR model and its methodology.
- Including a "Sample Usage" section with a Python code snippet, making it easier for users to quickly get started with the
efficient-speech/lite-whisper-smallmodel using thetransformerslibrary. The sample code was directly adapted from the provided GitHub repository's "Quick Start" guide.
These improvements aim to make the model card more informative and accessible for the community.