Instructions to use LongNN/TextSummarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LongNN/TextSummarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("LongNN/TextSummarization") model = AutoModelForSeq2SeqLM.from_pretrained("LongNN/TextSummarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f0b2ca813768f9afb3b897e4ec78a12c36847c1ec27180a5c4da4201760fddb
- Size of remote file:
- 1.2 GB
- SHA256:
- cf38ce157804977347f12099c2112d793cc40f4a35c683d53f3301e06714f71b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.