Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use Worldman/t5_70_articles with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Worldman/t5_70_articles with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Worldman/t5_70_articles") model = AutoModelForSeq2SeqLM.from_pretrained("Worldman/t5_70_articles", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 039e12360c18cc6a90eb0444f240b0cf215eac3e80730c9c046168cc6d99cff5
- Size of remote file:
- 3.18 kB
- SHA256:
- 9839ba51203323821d4be27fd9b8c4e16d9842c3386d673c19483487d073a0f9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.