Use MGM to represent Mini-Gemini

README.md

@@ -4,32 +4,32 @@ tags:
 - llama
 - generation
 datasets:
-- YanweiLi/Mini-Gemini-Instruction
+- YanweiLi/MGM-Instruction
 ---
 
-# Mini-Gemini-13B Model Card
+# MGM-13B Model Card
 <a href='https://github.com/dvlab-research/MiniGemini'><img src='https://img.shields.io/badge/Project-Code-violet'></a>
 <a href='https://mini-gemini.github.io/'><img src='https://img.shields.io/badge/Project-Page-Green'></a> 
 <a href='https://arxiv.org/pdf/2403.18814.pdf'><img src='https://img.shields.io/badge/Paper-Arxiv-red'></a>
 
 ## Model details
-Mini-Gemini supports a series of dense and MoE Large Language Models (LLMs) from 2B to 34B with HD image understanding, reasoning, and generation simultaneously.
+The framework supports a series of dense and MoE Large Language Models (LLMs) from 2B to 34B with HD image understanding, reasoning, and generation simultaneously.
 
-Normal resolution setting: [Mini-Gemini-2B](https://huggingface.co/YanweiLi/Mini-Gemini-2B), [Mini-Gemini-7B](https://huggingface.co/YanweiLi/Mini-Gemini-7B), [Mini-Gemini-8x7B](https://huggingface.co/YanweiLi/Mini-Gemini-8x7B), [Mini-Gemini-34B](https://huggingface.co/YanweiLi/Mini-Gemini-34B)
+Normal resolution setting: [MGM-2B](https://huggingface.co/YanweiLi/MGM-2B), [MGM-7B](https://huggingface.co/YanweiLi/MGM-7B), [MGM-8x7B](https://huggingface.co/YanweiLi/MGM-8x7B), [MGM-34B](https://huggingface.co/YanweiLi/MGM-34B)
 
-High resolution setting: [Mini-Gemini-7B-HD](https://huggingface.co/YanweiLi/Mini-Gemini-7B-HD), [Mini-Gemini-13B-HD](https://huggingface.co/YanweiLi/Mini-Gemini-13B-HD), [Mini-Gemini-8x7B-HD](https://huggingface.co/YanweiLi/Mini-Gemini-8x7B-HD), [Mini-Gemini-34B-HD](https://huggingface.co/YanweiLi/Mini-Gemini-34B-HD)
+High resolution setting: [MGM-7B-HD](https://huggingface.co/YanweiLi/MGM-7B-HD), [MGM-13B-HD](https://huggingface.co/YanweiLi/MGM-13B-HD), [MGM-8x7B-HD](https://huggingface.co/YanweiLi/MGM-8x7B-HD), [MGM-34B-HD](https://huggingface.co/YanweiLi/MGM-34B-HD)
 
 
 **Model type:**
-Mini-Gemini is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data.
+MGM is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data.
 
-Mini-Gemini empowers existing frameworks to support HD image understanding, reasoning, and generation simultaneously.
+It empowers existing frameworks to support HD image understanding, reasoning, and generation simultaneously.
 
 **Model version:**
-Mini-Gemini with LLM Vicuna-13B-v1.5
+MGM with LLM Vicuna-13B-v1.5
 
 **Model date:**
-Mini-Gemini-13B was trained on 03/2024.
+MGM-13B was trained on 03/2024.
 
 ## License
 Llama 2 is licensed under the LLAMA 2 Community License, 
@@ -40,10 +40,13 @@ https://github.com/dvlab-research/MiniGemini/issues
 
 ## Intended use
 **Primary intended uses:**
-The primary use of Mini-Gemini is research on large multimodal models and chatbots.
+The primary use is research on large multimodal models and chatbots.
 
 **Primary intended users:**
 The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.
 
 ## Training data
-This model is trained based on [Mini-Gemini-Instruction](https://huggingface.co/datasets/YanweiLi/Mini-Gemini-Instruction) dataset, please to the [Github](https://github.com/dvlab-research/MiniGemini) for more detail.
+This model is trained based on [MGM-Instruction](https://huggingface.co/datasets/YanweiLi/MGM-Instruction) dataset, please to the [Github](https://github.com/dvlab-research/MGM) for more detail.
+
+## Acknowledgement
+This project is not affiliated with Google LLC.