Automatic Speech Recognition
Transformers
PyTorch
Marathi
wav2vec2
speech_to_text
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use Tejas2000/SpeechRecog with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tejas2000/SpeechRecog with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Tejas2000/SpeechRecog")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Tejas2000/SpeechRecog") model = AutoModelForCTC.from_pretrained("Tejas2000/SpeechRecog") - Notebooks
- Google Colab
- Kaggle
| { | |
| "do_normalize": true, | |
| "feature_size": 1, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000 | |
| } |