Instructions to use nigo-ai/text_summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nigo-ai/text_summarizer with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nigo-ai/text_summarizer") model = AutoModelForSeq2SeqLM.from_pretrained("nigo-ai/text_summarizer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7fe8e061dca29ce3cac122cc5e5ea89215224c45f170ec2104a73e1bed576679
- Size of remote file:
- 558 MB
- SHA256:
- ba8f458782a83217c00ff507b01196c4b7f1a8bc32013a13ddde0eeae51dbc08
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.