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:
- 1e2d74400a6b463b443cf07bb1be98d384e4625344afad0411c1ac951cc3b11c
- Size of remote file:
- 5.5 kB
- SHA256:
- 35cc03612b7f32d98e24dad2241a09f1fb03ab2aef56cadb54287cffb3f8f9c2
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