Instructions to use web30india/LLM-Hindi-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use web30india/LLM-Hindi-Large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="web30india/LLM-Hindi-Large")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("web30india/LLM-Hindi-Large") model = AutoModelForSpeechSeq2Seq.from_pretrained("web30india/LLM-Hindi-Large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e45ec3041e3efd392f59be6f2a49b7cdc36d7be0ca8e05fb07df0041a3711535
- Size of remote file:
- 6.17 GB
- SHA256:
- 19ce1401808782bed996a352441d0ed88060aa2342db82201397e01b74d3cbb0
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