Automatic Speech Recognition
Transformers
PyTorch
Lithuanian
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use Tomas1234/common_voice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tomas1234/common_voice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Tomas1234/common_voice")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Tomas1234/common_voice") model = AutoModelForSpeechSeq2Seq.from_pretrained("Tomas1234/common_voice") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:587d9e64c5b4d8195e719009ce021965b61799a0b3d6008e570d82121232983c
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size 966995080
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