Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Portuguese
wav2vec2
Generated from Trainer
hf-asr-leaderboard
mozilla-foundation/common_voice_7_0
robust-speech-event
Eval Results (legacy)
Instructions to use lgris/wav2vec2-xls-r-pt-cv7-from-bp400h with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lgris/wav2vec2-xls-r-pt-cv7-from-bp400h with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lgris/wav2vec2-xls-r-pt-cv7-from-bp400h")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lgris/wav2vec2-xls-r-pt-cv7-from-bp400h") model = AutoModelForCTC.from_pretrained("lgris/wav2vec2-xls-r-pt-cv7-from-bp400h", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5eb92957d72f4dec8487c2e1fe8c0a44884a5cdcd31828786537f20dc68ef4fb
- Size of remote file:
- 2.93 kB
- SHA256:
- 23cb620bb159ee672b98ed1024f312996c67133d28a3802722a51fac02c55b43
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