Instructions to use Aditya02/Vistar_Marathi_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aditya02/Vistar_Marathi_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Aditya02/Vistar_Marathi_Model")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Aditya02/Vistar_Marathi_Model") model = AutoModelForSpeechSeq2Seq.from_pretrained("Aditya02/Vistar_Marathi_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9aebc3a37ea2febdab8cdf6b994c0203bec86bcf60385dd823efe0cd00461f5
- Size of remote file:
- 1.53 GB
- SHA256:
- d7079f4e8528325f0ead923300db6c757dd3c9dcb876a00dd26f9380d6f6b426
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