update terms

app.py

@@ -22,9 +22,11 @@ MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "4096"))
 DESCRIPTION = """\
 # ReFT-Chat (Llama-2 7B with 1K examples)
 
-### A chatbot built with ReFT and Llama-2 7B. It is trained with 1K training examples from the unpaired [Ultrafeedback dataset](https://huggingface.co/datasets/openbmb/UltraFeedback). It is not good at multi-turn conversations. You can train your own ReFT agent and share it on HuggingFace by following this [tutorial](https://github.com/stanfordnlp/pyreft/tree/main/examples/gradio/train_and_share.ipynb)!
+### What's ReFT-Chat?
+ReFT-Chat is a chatbot built with ReFT and Llama-2 7B. It is trained with 1K training examples from the unpaired [Ultrafeedback dataset](https://huggingface.co/datasets/openbmb/UltraFeedback). It is not good at multi-turn conversations. You can train your own ReFT agent and share it on HuggingFace by following this [tutorial](https://github.com/stanfordnlp/pyreft/tree/main/examples/gradio/train_and_share.ipynb)!
 
-#### This should only be used for research purposes. We did not conduct additional safety training with ReFT. We evaluate this model using [Alpaca-eval](https://github.com/tatsu-lab/alpaca_eval). Performance results can be found in [our ReFT paper](https://arxiv.org/abs/2404.03592). Our model inherits all the underlying risks associated with Llama. See terms outlined below.
+### Usage Terms
+This should only be used for research purposes. We did not conduct additional safety training with ReFT. We evaluate this model using [Alpaca-eval](https://github.com/tatsu-lab/alpaca_eval). Performance results can be found in [our ReFT paper](https://arxiv.org/abs/2404.03592). Our model inherits all the underlying risks associated with Llama. See terms outlined below.
 """
 
 LICENSE = """