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:
- f531a7a9a09f137673038958b426d7c175fa4c773e6a44c07bcc0683f27cb21a
- Size of remote file:
- 892 MB
- SHA256:
- 38173260aa6e784f4e812b03710ab49979a1fb63c4d3b492d32c8d88bb1fb1a1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.