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
- Xet hash:
- 3dadf8e88470a9f97576464b25c6b5cb19e0152929b6a84b44e66a87e0c564cf
- Size of remote file:
- 5.5 kB
- SHA256:
- 35578e1f3781162e825603b7bf23bbf33522e3303d584ca3309493901dee2d56
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