Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Lithuanian
whisper
lt-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use DeividasM/whisper-small-lt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeividasM/whisper-small-lt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DeividasM/whisper-small-lt")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("DeividasM/whisper-small-lt") model = AutoModelForSpeechSeq2Seq.from_pretrained("DeividasM/whisper-small-lt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c85a3e8e886c6142725c9e31905a7ad760dd93fbaf94fdc467c1df8d0afe4cd
- Size of remote file:
- 3.5 kB
- SHA256:
- da559874e3afa821642e838aae858490c6ba65f88eba7374568750c4de3c3efd
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