Merge pull request #647 from OptimalScale/shizhe-update-qrcode20

update qrcode

README.md

@@ -21,7 +21,7 @@
 [![Doc](https://img.shields.io/badge/Website-Doc-ff69b4.svg)](https://optimalscale.github.io/LMFlow/)
 [![Embark](https://img.shields.io/badge/Discord-LMFlow-%237289da.svg?logo=discord)](https://discord.gg/u9VJNpzhvA)
 [![slack badge](https://img.shields.io/badge/Slack-Join-blueviolet?logo=slack&amp)](https://join.slack.com/t/lmflow/shared_invite/zt-1wju9nicy-woXbNtS~5MavHSAtiMxmxQ)
-[![WeChat badge](https://img.shields.io/badge/WeChat-Join-brightgreen?logo=wechat&amp)](https://i.ibb.co/JvXwWg9/Wechat-IMG1110.jpg)
+[![WeChat badge](https://img.shields.io/badge/WeChat-Join-brightgreen?logo=wechat&amp)](https://i.ibb.co/kKvGhPr/Wechat-IMG1129.jpg)
 
 An extensible, convenient, and efficient toolbox for finetuning large machine learning models, designed to be user-friendly, speedy and reliable, and accessible to the entire community.
 
@@ -31,11 +31,11 @@ An extensible, convenient, and efficient toolbox for finetuning large machine le
 
 
 ## Latest News
-* [2023-09-11] Support [speculative decoding](https://arxiv.org/abs/2211.17192). Check out [speculative_decoding](https://github.com/OptimalScale/LMFlow/blob/main/scripts/speculative_decoding/README.md) for the usage and acceleration details.
+* [2023-09-11] :rocket: Support [speculative decoding](https://arxiv.org/abs/2211.17192). Check out [speculative_decoding](https://github.com/OptimalScale/LMFlow/blob/main/scripts/speculative_decoding/README.md) for the usage and acceleration details. :rocket: 
 * [2023-08-14] Support long context inference with position interpolation (Linear & NTK scaling ) for LLaMA models. Check out [postion_interpolation](https://github.com/OptimalScale/LMFlow/blob/main/readme/Position_Interpolation.md) for more details.
 * [2023-08-07] Support [Flash Attention-2](https://crfm.stanford.edu/2023/07/17/flash2.html). Check out [flash_attention](https://github.com/OptimalScale/LMFlow/blob/main/readme/flash_attn2.md) for more details.
 * [2023-08-02] Support [Llama2](https://ai.meta.com/llama/), [ChatGLM2](https://huggingface.co/THUDM/chatglm2-6b), and [Baichuan](https://huggingface.co/baichuan-inc/Baichuan-7B) models.
-* [2023-07-23] :rocket: [LMFlow multimodal chatbot](https://github.com/OptimalScale/LMFlow/blob/main/scripts/run_vis_chatbot_gradio_minigpt4.sh) is now available! Support multimodal inputs of images and texts. [Online Demo](http://multimodal.lmflow.online) is also provided (We hold the service on a single GPU, hence one may experience "queuing" or "application busy" sometimes when multiple users are accessing at the same time, please wait and attempt again later when such event happens) :rocket: ![image](https://github.com/OptimalScale/LMFlow/blob/rpan-vision-encoder/assets/multimodal-chatbot-demo.gif)
+* [2023-07-23] [LMFlow multimodal chatbot](https://github.com/OptimalScale/LMFlow/blob/main/scripts/run_vis_chatbot_gradio_minigpt4.sh) is now available! Support multimodal inputs of images and texts. [Online Demo](http://multimodal.lmflow.online) is also provided (We hold the service on a single GPU, hence one may experience "queuing" or "application busy" sometimes when multiple users are accessing at the same time, please wait and attempt again later when such event happens)![image](https://github.com/OptimalScale/LMFlow/blob/rpan-vision-encoder/assets/multimodal-chatbot-demo.gif)
 * [2023-06-22]  [LMFlow paper](https://arxiv.org/abs/2306.12420) is out! Check out our implementation details at https://arxiv.org/abs/2306.12420
 * [2023-06-16] Our finetuned Robin-33B-V2 scored an impressive 64.1 on the Huggingface LLM leaderboard in our offline evaluation, outperforming major open-source LLMs! All checkpoints (7B, 13B, 33B, and 65B) are [released](https://huggingface.co/OptimalScale)! Checkout the performance [here](https://medium.com/@hkust.ml/robin-v2-launches-achieves-unparalleled-performance-on-openllm-4f6886e822c1).
 * [2023-06-07] LMFlow is now officially available on PyPI! Install it with `pip install lmflow-finetune`!