Update README.md

README.md

@@ -12,10 +12,10 @@ model-index:
 
 # Graphcore/bert-base-uncased
 
-This model is a pre-trained BERT-Base trained in two phases on the [Graphcore/wikipedia-bert-128](https://huggingface.co/datasets/Graphcore/wikipedia-bert-128) and [Graphcore/wikipedia-bert-512](https://huggingface.co/datasets/Graphcore/wikipedia-bert-512) datasets.
+Optimum Graphcore is a new open-source library and toolkit that enables developers to access IPU-optimized models certified by Hugging Face. It is an extension of Transformers, providing a set of performance optimization tools enabling maximum efficiency to train and run models on Graphcore’s IPUs - a completely new kind of massively parallel processor to accelerate machine intelligence. Learn more about how to take train Transformer models faster with IPUs at [hf.co/hardware/graphcore](https://huggingface.co/hardware/graphcore).
+
+Through HuggingFace Optimum, Graphcore released ready-to-use IPU-trained model checkpoints and IPU configuration files to make it easy to train models with maximum efficiency in the IPU. Optimum shortens the development lifecycle of your AI models by letting you plug-and-play any public dataset and allows a seamless integration to our State-of-the-art hardware giving you a quicker time-to-value for your AI project.
 
-It was trained on a Graphcore IPU-POD16 using [`optimum-graphcore`](https://github.com/huggingface/optimum-graphcore).
-Graphcore and Hugging Face are working together to make training of Transformer models on IPUs fast and easy. Learn more about how to take advantage of the power of Graphcore IPUs to train Transformers models at [hf.co/hardware/graphcore](https://huggingface.co/hardware/graphcore).
 
 ## Model description
 
@@ -28,6 +28,11 @@ It reduces the need of many engineering efforts for building task specific archi
 
 ## Training and evaluation data
 
+This model is a pre-trained BERT-Base trained in two phases on the [Graphcore/wikipedia-bert-128](https://huggingface.co/datasets/Graphcore/wikipedia-bert-128) and [Graphcore/wikipedia-bert-512](https://huggingface.co/datasets/Graphcore/wikipedia-bert-512) datasets.
+
+It was trained on a Graphcore IPU-POD16 using [`optimum-graphcore`](https://github.com/huggingface/optimum-graphcore).
+Graphcore and Hugging Face are working together to make training of Transformer models on IPUs fast and easy. Learn more about how to take advantage of the power of Graphcore IPUs to train Transformers models at [hf.co/hardware/graphcore](https://huggingface.co/hardware/graphcore).
+
 Trained on wikipedia datasets:
 - [Graphcore/wikipedia-bert-128](https://huggingface.co/datasets/Graphcore/wikipedia-bert-128)
 - [Graphcore/wikipedia-bert-512](https://huggingface.co/datasets/Graphcore/wikipedia-bert-512)