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:
- 4f58ab7ea565f283ec597618ed9dd0f4c3150fe6f5b44d8eaaa987167d256c00
- Size of remote file:
- 1.26 GB
- SHA256:
- 08de7da709cb1c87182ea525062fcd525beeade5ce32613467ec0bcc59e40f04
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