Automatic Speech Recognition
Transformers
Safetensors
lite-whisper
feature-extraction
audio
whisper
hf-asr-leaderboard
custom_code
Instructions to use efficient-speech/lite-whisper-small-acc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use efficient-speech/lite-whisper-small-acc 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-acc", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("efficient-speech/lite-whisper-small-acc", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Improve model card with abstract and usage example
#1
by nielsr HF Staff - opened
This PR enhances the model card by incorporating the paper's abstract, a direct link to the Hugging Face paper page, and a clear code snippet for sample usage from the GitHub repository. These additions provide more comprehensive information for users and showcase how to quickly get started with the model using the transformers library.