Update app.py

app.py

@@ -31,11 +31,7 @@ conforms to common characteristics.
 I used all variants of the open-source GPT-2 model except xl size to compute the PPL (both text-level and sentence-level PPLs) of the collected \
 texts. It is observed that, regardless of whether it is at the text level or the sentence level, the content generated by LLMs have relatively \
 lower PPLs compared to the text written by humans. LLM captured common patterns and structures in the text it was trained on, and is very good at \
-reproducing them. As a result, text generated by LLMs have relatively concentrated low PPLs.
-
-Humans have the ability to express themselves in a wide variety of ways, depending on the context, audience, and purpose of the text they are \
-writing. This can include using creative or imaginative elements, such as metaphors, similes, and unique word choices, which can make it more \
-difficult for GPT2 to predict. The PPL distributions of text written by humans and text generated by LLMs are shown in the figure below.\
+reproducing them. As a result, text generated by LLMs have relatively concentrated low PPLs.\
 """
 
 
@@ -124,11 +120,11 @@ with gr.Blocks() as demo:
         ## Detect text generated using LLMs 🤖
 
         Linguistic features such as Perplexity and other SOTA methods such as GLTR were used to classify between Human written and LLM Generated \
-        texts. This solution scored an ROC of 0.956 and 8th position in the DAIGT LLM Competition on Kaggle. Fork of and credits to this github repo
+        texts. This solution scored an ROC of 0.956 and 8th position in the DAIGT LLM Competition on Kaggle.
 
+        - Source & Credits: [https://github.com/Hello-SimpleAI/chatgpt-comparison-detection](https://github.com/Hello-SimpleAI/chatgpt-comparison-detection)
         - Competition: [https://www.kaggle.com/competitions/llm-detect-ai-generated-text/leaderboard](https://www.kaggle.com/competitions/llm-detect-ai-generated-text/leaderboard)
         - Solution WriteUp: [https://www.kaggle.com/competitions/llm-detect-ai-generated-text/discussion/470224](https://www.kaggle.com/competitions/llm-detect-ai-generated-text/discussion/470224)
-        - Source & Credits: [https://github.com/Hello-SimpleAI/chatgpt-comparison-detection](https://github.com/Hello-SimpleAI/chatgpt-comparison-detection)
 
         ### Linguistic Analysis: Language Model Perplexity
         The perplexity (PPL) is commonly used as a metric for evaluating the performance of language models (LM). It is defined as the exponential \