Instructions to use Priyanship/eval_cache_hindi_only with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Priyanship/eval_cache_hindi_only with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Priyanship/eval_cache_hindi_only")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Priyanship/eval_cache_hindi_only") model = AutoModelForCTC.from_pretrained("Priyanship/eval_cache_hindi_only", device_map="auto") - Notebooks
- Google Colab
- Kaggle
eval_cache_hindi_only / transliteratedevalonlyhindi_indicwav2vec_MUCS_warmup500_s300shuff100_3707642.out
| File "/scratch/elec/puhe/p/palp3/MUCS/eval_script_indicwav2vec.py", line 695 | |
| ''' | |
| IndentationError: unexpected indent | |