Automatic Speech Recognition
Transformers
Safetensors
lite-whisper
feature-extraction
audio
whisper
hf-asr-leaderboard
custom_code
Eval Results
Instructions to use efficient-speech/lite-whisper-large-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use efficient-speech/lite-whisper-large-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="efficient-speech/lite-whisper-large-v3", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("efficient-speech/lite-whisper-large-v3", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add Open ASR Leaderboard evaluation results
#4
by SaylorTwift HF Staff - opened
No description provided.