Instructions to use jbhargav/gujarati-indicbart-5000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jbhargav/gujarati-indicbart-5000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jbhargav/gujarati-indicbart-5000") model = AutoModelForSeq2SeqLM.from_pretrained("jbhargav/gujarati-indicbart-5000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 266e4310f2c8eb6a9aa5819021d21f39ad4ca4a2c49961e65089633722dd21e2
- Size of remote file:
- 1.76 GB
- SHA256:
- a9215b8df889b89b4896acf3659dc9fda3f35b4c65e6cdad8567bf4197fa36d5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.