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:
- 373b79199e23e61b593e799ff8788a0b258517eb81e39148fe2afc8ff429fb64
- Size of remote file:
- 1.26 GB
- SHA256:
- f5e933f24a1e1d86291baac26c788aea3eaf9a0a1f4cfa37fb7e5a3559f04ffb
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