Instructions to use ieuniversity/pangea_summarization_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ieuniversity/pangea_summarization_model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ieuniversity/pangea_summarization_model") model = AutoModelForSeq2SeqLM.from_pretrained("ieuniversity/pangea_summarization_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84ea5e0cfc860aa5521f7b291b07f6d6fbaee8cf4f2188d55d9421a4174b58c4
- Size of remote file:
- 242 MB
- SHA256:
- 106fa4bfbf021e934b184c0912ef2b3c2f36d7d44bae74e555d7c9a304e70d82
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.