wrap news

README.md

@@ -44,16 +44,19 @@ Large Model for All. See our [vision](https://github.com/OptimalScale/LMFlow#vis
 * [2023-05-08] Release [LMFlow Benchmark](https://medium.com/@hkust.ml/lmflow-benchmark-an-automatic-evaluation-framework-for-open-source-llms-ef5c6f142418), an automatic evaluation framework for open-source chat-style LLMs. [Benchmark results](https://docs.google.com/spreadsheets/d/1JYh4_pxNzmNA9I0YM2epgRA7VXBIeIGS64gPJBg5NHA/edit#gid=0) on 31 popular models are reported. [Participate in LMFlow Benchmark](https://github.com/OptimalScale/LMFlow#33-lmflow-benchmark).
 * [2023-04-21] Release [Robin-7B](http://lmflow.org:5000/robin-7b.tar.gz) (based on LLaMA-7B), and two models for commercial use: Parakeets-2.7B (based on GPT-NEO-2.7B) and Cokatoo-7B (based on StableLM-7B) [Download here](https://github.com/OptimalScale/LMFlow/tree/main#model-zoo)
 * [2023-04-10] We propose a new alignment algorithm: [Reward rAnked FineTuning (RAFT)](https://optimalscale.github.io/LMFlow/examples/raft.html), which is more efficient than conventional (PPO-based) RLHF. [[Paper](https://arxiv.org/abs/2304.06767)]
-<!-- * [2023-04-02] [Web service](https://lmflow.com/) is online! -->
-<!-- * [2023-04-01] Release three instruction-tuned checkpoints and three medical checkpoints in [model zoo](https://github.com/OptimalScale/LMFlow#model-zoo): LLaMA-7B-tuned, LLaMA-13B-tuned, LLaMA-33B-tuned, LLaMA-7B-medical, LLaMA-13B-medical, and LLaMA-33B-medical. -->
-* [2023-03-27] Release code and checkpoints - [version 0.0.1](https://optimalscale.github.io/LMFlow/)! [Our tasked-tuned model beats ChatGPT on medical domain](https://github.com/OptimalScale/LMFlow#model-performance).
-<!-- * [2023-03-27] Support full tuning and lora tuning for all decoder models.
-* [2023-03-27] [Tasked tuned model beats ChatGPT on medical domain](https://github.com/OptimalScale/LMFlow#model-performance). -->
-<!-- * [2023-04-15] Inference: Support streaming output and ChatGLM. -->
 
-## Demos
 
 
+<details> <summary>More news...</summary>
+* [2023-04-15] Inference: Support streaming output and ChatGLM.
+* [2023-04-02] [Web service](https://lmflow.com/) is online! -->
+* [2023-04-01] Release three instruction-tuned checkpoints and three medical checkpoints in [model zoo](https://github.com/OptimalScale/LMFlow#model-zoo): LLaMA-7B-tuned, LLaMA-13B-tuned, LLaMA-33B-tuned, LLaMA-7B-medical, LLaMA-13B-medical, and LLaMA-33B-medical.
+* [2023-03-27] Support full tuning and lora tuning for all decoder models.
+* [2023-03-27] [Tasked tuned model beats ChatGPT on medical domain](https://github.com/OptimalScale/LMFlow#model-performance).
+* [2023-03-27] Release code and checkpoints - [version 0.0.1](https://optimalscale.github.io/LMFlow/)! [Our tasked-tuned model beats ChatGPT on medical domain](https://github.com/OptimalScale/LMFlow#model-performance).
+</details>
+
+## Demos
 We provide four kinds of demos which include
 - Online Service: If you don't want to run any code and just want to try our models, we deploy our instruction-tuned LLaMA you to have a try.
 - Colab Chatbot (shell): An interactive shell-based chatbot for you to easily deploy a chatbot on colab.