Automatic Speech Recognition
Transformers
Oriya
wav2vec2
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use varunril/odia_transcript_generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use varunril/odia_transcript_generation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="varunril/odia_transcript_generation")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("varunril/odia_transcript_generation") model = AutoModelForCTC.from_pretrained("varunril/odia_transcript_generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from varunril/odia_transcript_generation: direct link, hf CLI and curl.
- Browser
- Download file 158 Bytes
-
https://huggingface.co/varunril/odia_transcript_generation/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://varunril/odia_transcript_generation/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/varunril/odia_transcript_generation/resolve/main/preprocessor_config.json
158 Bytes
| { | |
| "do_normalize": true, | |
| "feature_size": 1, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000 | |
| } | |