Instructions to use Linggg/t5_summary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Linggg/t5_summary with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Linggg/t5_summary") model = AutoModelForSeq2SeqLM.from_pretrained("Linggg/t5_summary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
1d5d2ec | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:b9c6e5c109ed0ed42268a2e73bd5f8dba6604587013cf6ab0c2f0dc9adfd6f5a
size 16330636
|