google
/

flan-t5-large

Text2Text Generation

text-generation-inference

Inference Endpoints

Model card Files Files and versions Community

ybelkada commited on Oct 21, 2022

Commit

5ae0274

•

1 Parent(s): 99ffe3a

Update README.md

Files changed (1) hide show

README.md +2 -1

README.md CHANGED Viewed

@@ -100,7 +100,8 @@ license: apache-2.0
 # TL;DR
-If you already know T5, FLAN-T5 is just better at everything! It is a **bigger model (+ XX parameters)** was trained on **more tasks (+ XX )**, **more data (+ XX tokens)** and **more languags (+ XX languages)**. As mentioned in the first few lines of the abstract :
 >  Flan-PaLM 540B achieves state-of-the-art performance on several benchmarks, such as 75.2% on five-shot MMLU. We also publicly release Flan-T5 checkpoints,1 which achieve strong few-shot performance even compared to much larger models, such as PaLM 62B. Overall, instruction finetuning is a general method for improving the performance and usability of pretrained language models.
 **Disclaimer**: Content from **this** model card has been written by the Hugging Face team, and parts of it were copy pasted from the [T5 model card](https://huggingface.co/t5-large).

 # TL;DR
+If you already know T5, FLAN-T5 is just better at everything.
+As mentioned in the first few lines of the abstract :
 >  Flan-PaLM 540B achieves state-of-the-art performance on several benchmarks, such as 75.2% on five-shot MMLU. We also publicly release Flan-T5 checkpoints,1 which achieve strong few-shot performance even compared to much larger models, such as PaLM 62B. Overall, instruction finetuning is a general method for improving the performance and usability of pretrained language models.
 **Disclaimer**: Content from **this** model card has been written by the Hugging Face team, and parts of it were copy pasted from the [T5 model card](https://huggingface.co/t5-large).