Instructions to use google/flan-t5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/flan-t5-large with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-large") model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-large") - Notebooks
- Google Colab
- Kaggle
Use T5_large for training and output outputs.loss as NAN.
#19
by Swithun - opened
Why is T5_large loaded for training, e.g. outputs = model(input_ids, labels = target_ids) and the output outputs.loss is NAN. But on the same dataset loaded T5_small model outputs.loss is correct.
