Automatic Speech Recognition
Transformers
PyTorch
Portuguese
wav2vec2
audio
speech
portuguese-speech-corpus
PyTorch
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use lgris/bp500-base10k_voxpopuli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lgris/bp500-base10k_voxpopuli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lgris/bp500-base10k_voxpopuli")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lgris/bp500-base10k_voxpopuli") model = AutoModelForCTC.from_pretrained("lgris/bp500-base10k_voxpopuli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1115a3e4f0cc3cec7ccc6b03a023419cfde6a36645aa0007d230017f7bab64f6
- Size of remote file:
- 378 MB
- SHA256:
- 1ac25d86ddfb328a9dcb2a0c8233263b41ef6da1db4bc7edc99cdcb0fe539d9f
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