Update README.md

README.md

@@ -9,14 +9,13 @@ model-index:
   results: []
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-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
 
-# clm_output_medium
+# Graphcore/gpt2-medium-wikitext-103
+
+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.
+
+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.
 
-This model is a fine-tuned version of [gpt2-medium](https://huggingface.co/gpt2-medium) on the [wikitext-103-raw-v1](https://huggingface.co/datasets/wikitext) dataset.
-It achieves the following results on the evaluation set:
-- Loss: 2.6973
 
 ## Model description
 
@@ -24,11 +23,11 @@ GPT2 is a large transformer-based language model. It is built using transformer
  
 Paper link : [Language Models are Unsupervised Multitask Learners](https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf) 
 
-## Intended uses & limitations
-
-More information needed
 
 ## Training and evaluation data
+This model is a fine-tuned version of [gpt2-medium](https://huggingface.co/gpt2-medium) on the [wikitext-103-raw-v1](https://huggingface.co/datasets/wikitext) dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.6973
 
 [wikitext-103-raw-v1](https://huggingface.co/datasets/wikitext) dataset