Instructions to use research-dump/flan-t5-large_fold_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/flan-t5-large_fold_0 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("research-dump/flan-t5-large_fold_0") model = AutoModelForSeq2SeqLM.from_pretrained("research-dump/flan-t5-large_fold_0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a454b2a276537b60f192713c1fefecb41cf4f50a03358684d6f1d374a499c2fa
- Size of remote file:
- 1.57 GB
- SHA256:
- fe5fea79a4384af525a734832ba25085980382f7842187e0ee0d576494e65409
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.