Instructions to use Adarsh203/mBART_SUM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Adarsh203/mBART_SUM with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Adarsh203/mBART_SUM") model = AutoModelForSeq2SeqLM.from_pretrained("Adarsh203/mBART_SUM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6fb7bb3cb87b0803c1c328069fb1587fb49f04457487c66adb57aaf9f16cf9ec
- Size of remote file:
- 17.1 MB
- SHA256:
- 9c83c5677c05450e639cd3be9246b917583928b0c62831e76c03e5986cc057ce
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