Instructions to use Anujgr8/indic-bert-large-cs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Anujgr8/indic-bert-large-cs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Anujgr8/indic-bert-large-cs")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Anujgr8/indic-bert-large-cs") model = AutoModelForCTC.from_pretrained("Anujgr8/indic-bert-large-cs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Anujgr8/indic-bert-large-cs: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/Anujgr8/indic-bert-large-cs/resolve/main/training_args.bin
- Command line
-
hf download hf://Anujgr8/indic-bert-large-cs/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Anujgr8/indic-bert-large-cs/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 05582db293a77a9a03339dadd9a74a43d8e05dfb816445d06f42e8e966a5f1b8
- Size of remote file:
- 4.54 kB
- SHA256:
- b449a41d211dd20f13b341accbca7ba30055bce67caf30e815c71776faddd4f8
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