Instructions to use jsaizant/ETEREX_TEXT2STORY with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jsaizant/ETEREX_TEXT2STORY with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jsaizant/ETEREX_TEXT2STORY") model = AutoModelForSeq2SeqLM.from_pretrained("jsaizant/ETEREX_TEXT2STORY") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3305fd1a44336d066d3cbdd2da2439a2838bc2c8e4fac584c5f123ed7f0c50d8
- Size of remote file:
- 1.63 GB
- SHA256:
- ad02e42f088537a0c24b9aa3985eeb205c08e12486a4a9cea160d4af23114c98
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