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:
- 392562f13bd8a4969a3ee3457d8d0f2406ff4b5ffb000391ece7e43733a54ae8
- Size of remote file:
- 3.06 GB
- SHA256:
- 2f088effc4d76c88d659f157e6ca6a78e05fc5131a78e40da1a92a301ca56d65
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