Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
mozilla-foundation/common_voice_8_0
Generated from Trainer
pa-IN
robust-speech-event
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use DrishtiSharma/wav2vec2-large-xls-r-300m-pa-IN-dx1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DrishtiSharma/wav2vec2-large-xls-r-300m-pa-IN-dx1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DrishtiSharma/wav2vec2-large-xls-r-300m-pa-IN-dx1")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("DrishtiSharma/wav2vec2-large-xls-r-300m-pa-IN-dx1") model = AutoModelForCTC.from_pretrained("DrishtiSharma/wav2vec2-large-xls-r-300m-pa-IN-dx1") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 100.0, | |
| "train_loss": 0.7658213693124276, | |
| "train_runtime": 5843.2467, | |
| "train_samples": 856, | |
| "train_samples_per_second": 14.649, | |
| "train_steps_per_second": 0.924 | |
| } |