Automatic Speech Recognition
Transformers
Safetensors
lite-whisper
feature-extraction
audio
whisper
hf-asr-leaderboard
custom_code
Instructions to use efficient-speech/lite-whisper-tiny-acc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use efficient-speech/lite-whisper-tiny-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-tiny-acc", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("efficient-speech/lite-whisper-tiny-acc", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a7484ca67b6022955ec0231f2cef19020673d9b81f47f17d62afc2ce3e9f0bf
- Size of remote file:
- 230 MB
- SHA256:
- bb4bee317df57c572ce7329e6e2860ba3aafa5f8c8241cfaea60b6870b0981eb
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