Update README.md

README.md

@@ -25,23 +25,24 @@ It achieves the following results on the evaluation set:
 - Rougelsum: 0.1842
 - Generated Length: 19.0
 
-## Model description
+## Model Description
 
-The developers of the Text-To-Text Transfer Transformer (T5) write:
+The developers of the Text-To-Text Transfer Transformer (T5) [write](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html): 
 
-With T5, we propose reframing all NLP tasks into a unified text-to-text-format where the input and output are always text strings, in contrast to BERT-style models that can only output either a class label or a span of the input. Our text-to-text framework allows us to use the same model, loss function, and hyperparameters on any NLP task.
+> With T5, we propose reframing all NLP tasks into a unified text-to-text-format where the input and output are always text strings, in contrast to BERT-style models that can only output either a class label or a span of the input. Our text-to-text framework allows us to use the same model, loss function, and hyperparameters on any NLP task.
 
-T5-Small is the checkpoint with 60 million parameters.
+T5-Small is the checkpoint with 60 million parameters. 
 
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
+- **Developed by:** Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu. See [associated paper](https://jmlr.org/papers/volume21/20-074/20-074.pdf) and [GitHub repo](https://github.com/google-research/text-to-text-transfer-transformer#released-model-checkpoints)
+- **Model type:** Language model
+- **Language(s) (NLP):** English, French, Romanian, German
+- **License:** Apache 2.0
+- **Related Models:** [All T5 Checkpoints](https://huggingface.co/models?search=t5)
+- **Resources for more information:**
+  - [Research paper](https://jmlr.org/papers/volume21/20-074/20-074.pdf)
+  - [Google's T5 Blog Post](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) 
+  - [GitHub Repo](https://github.com/google-research/text-to-text-transfer-transformer)
+  - [Hugging Face T5 Docs](https://huggingface.co/docs/transformers/model_doc/t5)
 
 ### Training hyperparameters