Automatic Speech Recognition
Transformers
PyTorch
Lithuanian
whisper
whisper-event
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use DeividasM/whisper-medium-lt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeividasM/whisper-medium-lt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DeividasM/whisper-medium-lt")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("DeividasM/whisper-medium-lt") model = AutoModelForSpeechSeq2Seq.from_pretrained("DeividasM/whisper-medium-lt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c6a5be9185aaa2bd544ba51acac5e300f6050262555e0da5e979ef0b5610ac8
- Size of remote file:
- 3.64 kB
- SHA256:
- f7dd0175a358b3c7468d01bd6e3b7f1ebf4d7cb31a362ebd711d1d6ba50c566e
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