Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
mozilla-foundation/common_voice_7_0
Generated from Trainer
Instructions to use jcmc/wav2vec2-xls-r-1b-ir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jcmc/wav2vec2-xls-r-1b-ir with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jcmc/wav2vec2-xls-r-1b-ir")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jcmc/wav2vec2-xls-r-1b-ir") model = AutoModelForCTC.from_pretrained("jcmc/wav2vec2-xls-r-1b-ir", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 397 Bytes
b932980 2b29e30 b932980 2b29e30 b932980 2b29e30 b932980 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"epoch": 99.98,
"eval_loss": 1.656851053237915,
"eval_runtime": 24.6949,
"eval_samples": 509,
"eval_samples_per_second": 20.612,
"eval_steps_per_second": 2.592,
"eval_wer": 0.862331575864089,
"train_loss": 1.9993535804748535,
"train_runtime": 10079.8406,
"train_samples": 1035,
"train_samples_per_second": 10.268,
"train_steps_per_second": 0.317
} |