internetoftim commited on
Commit
8a95cfe
1 Parent(s): 347a424

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +15 -4
README.md CHANGED
@@ -1,16 +1,27 @@
1
- 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).
 
 
2
 
3
- # GPT2 Medium model IPU config
4
 
5
- This model contains just the `IPUConfig` files for running the [gpt2-medium](https://huggingface.co/gpt2-medium) model on Graphcore IPUs.
 
 
6
 
7
- **This model contains no model weights, only an IPUConfig.**
8
 
9
  ## Model description
10
  GPT2 is a large transformer-based language model. It is built using transformer decoder blocks. BERT, on the other hand, uses transformer encoder blocks. It adds Layer normalisation to the input of each sub-block, similar to a pre-activation residual networks and an additional layer normalisation.
11
 
12
  Paper link : [Language Models are Unsupervised Multitask Learners](https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf)
13
 
 
 
 
 
 
 
 
 
14
  ## Usage
15
 
16
  ```
 
1
+ ---
2
+ license: apache-2.0
3
+ ---
4
 
5
+ # Graphcore/roberta-base-ipu
6
 
7
+ 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).
8
+
9
+ 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.
10
 
 
11
 
12
  ## Model description
13
  GPT2 is a large transformer-based language model. It is built using transformer decoder blocks. BERT, on the other hand, uses transformer encoder blocks. It adds Layer normalisation to the input of each sub-block, similar to a pre-activation residual networks and an additional layer normalisation.
14
 
15
  Paper link : [Language Models are Unsupervised Multitask Learners](https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf)
16
 
17
+
18
+
19
+ ## Intended uses & limitations
20
+
21
+ This model contains just the `IPUConfig` files for running the [HuggingFace/gpt2-medium](https://huggingface.co/gpt2-medium) model on Graphcore IPUs.
22
+
23
+ **This model contains no model weights, only an IPUConfig.**
24
+
25
  ## Usage
26
 
27
  ```