Automatic Speech Recognition
Transformers
PyTorch
Portuguese
wav2vec2
audio
speech
portuguese-speech-corpus
PyTorch
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use lgris/bp500-xlsr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lgris/bp500-xlsr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lgris/bp500-xlsr")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lgris/bp500-xlsr") model = AutoModelForCTC.from_pretrained("lgris/bp500-xlsr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from lgris/bp500-xlsr: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/lgris/bp500-xlsr/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://lgris/bp500-xlsr/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/lgris/bp500-xlsr/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- f4083f54af932db5459b7c9f8569c261f060067bfa3a1f4c530ce77df2fbc0d0
- Size of remote file:
- 1.26 GB
- SHA256:
- d11e94f7cd09a27665d2a0f01c508d0f7411e02df0ef82aedff362f97460ade0
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