Update description.md

description.md

@@ -1 +1,30 @@
-This is an example functionality for a machine vision model app (OFA) using links to image files to write a description of what the model sees based on the classifiers associated with the training data. The model use case reads a URL link to an image file, runs the object detection model to identify the subject matter of the image, and returns the model description. 
+OFA (Open-domain Feature-based Architecture) is an open-source, unified sequence-to-sequence learning framework developed by Open-domain Feature-based Architecture System (OFA-Sys). 
+
+It was released in ICML 2022[1]. 
+
+OFA is designed to unify modalities and tasks such as
+image captioning, 
+o VQA, visual grounding, 
+o text-to-image generation, 
+o text classification, 
+o text generation, 
+o image classification. 
+
+It provides step-by-step instructions for pretraining and finetuning with checkpoints available from both official repository and Hugging Face. [2] 
+
+OFA also provides online demos for interactive experience with its pretrained and finetuned models. [3] 
+
+Furthermore, it offers Colab notebooks to understand the procedures better. OFA is even more powerful with the release of MuE (Multi-modal Embeddings) which accelerates OFA with little performance degradation. [1] 
+
+It also provides OFA-OCR for Chinese text recognition [1] and MMSpeech, an ASR pre-training method based on OFA. [1] 
+
+Moreover, a Chinese version of OFA is released. [1]
+
+
+References:
+
+[1] https://github.com/OFA-Sys/OFA
+
+[2] https://github.com/OFA-Sys
+
+[3] https://github.com/OFA-Sys/OFA/blob/main/colab.md