Instructions to use Worldman/pega_70_articles with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Worldman/pega_70_articles with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Worldman/pega_70_articles") model = AutoModelForSeq2SeqLM.from_pretrained("Worldman/pega_70_articles", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52f42715d5d62ed3300b527e381923a40826cf9ce66272850e63c21feb830559
- Size of remote file:
- 3.18 kB
- SHA256:
- 22332c21d185ad04a2f77089954e045dde262f027709a75dca4b499ead122b10
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.