Instructions to use heskielsvn/bert2bert-cased-project-SamSum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use heskielsvn/bert2bert-cased-project-SamSum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("heskielsvn/bert2bert-cased-project-SamSum") model = AutoModelForSeq2SeqLM.from_pretrained("heskielsvn/bert2bert-cased-project-SamSum") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ddd9750e2f8d1261df0c17d4a1c17a479b0b656cfa6cb46f6c8cbef6f6bf479c
- Size of remote file:
- 980 MB
- SHA256:
- 574e6279c661f36f1a7b03948d714099d003edd5c203d94a5710f624eada19dd
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