Automatic Speech Recognition
Transformers
PyTorch
JAX
French
wav2vec2
audio
hf-asr-leaderboard
mozilla-foundation/common_voice_6_0
robust-speech-event
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use bonvent/test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bonvent/test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bonvent/test2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("bonvent/test2") model = AutoModelForCTC.from_pretrained("bonvent/test2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1883a3fcd8f4792cd62189b7278e62afb65cf08c5907a702aaed025e68e232c
- Size of remote file:
- 1.26 GB
- SHA256:
- 37244d7e17dd8027f9e5dcc6e2556f5cee16f8d41a944f0df6f0d5ef7c6a51bb
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