Automatic Speech Recognition
Transformers
PyTorch
French
wav2vec2
mozilla-foundation/common_voice_8_0
Generated from Trainer
Eval Results (legacy)
Instructions to use Plim/test_lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Plim/test_lm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Plim/test_lm")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Plim/test_lm") model = AutoModelForCTC.from_pretrained("Plim/test_lm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed7b5cb7bb2234ee5b9ce2f83c71bbe788fdb28dbf2d69e7f3518e79fd7ebba0
- Size of remote file:
- 3.85 GB
- SHA256:
- 4a7ac9a4075231a9b1f2ef054fe1161fdf7235b6c7bd018f7505d44da3332960
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