update readme file

README.md

@@ -10,15 +10,10 @@ pinned: false
 hf_oauth: true
 hf_oauth_scopes:
   - inference-api
-short_description: Abstractive TL;DR summarizer for chemistry research abstracts.
+short_description: TL;DR summarizer for chemistry research abstracts
 ---
 
-Lit2Vec TL;DR is an abstractive summarization tool for chemistry research abstracts, built using Gradio and a fine-tuned DistilBART model. It generates concise, structured summaries capturing the **methods**, **results**, and **significance** of scientific papers.
-
-This app uses models hosted on the 🤗 [Hugging Face Hub](https://huggingface.co/Bocklitz-Lab/lit2vec-tldr-bart-model) and supports reproducible, legally compliant summarization data. Ideal for knowledge graph construction, semantic indexing, and literature triage in chemical sciences.
 
-- 🔬 Model: [`Bocklitz-Lab/lit2vec-tldr-bart-model`](https://huggingface.co/Bocklitz-Lab/lit2vec-tldr-bart-model)  
-- 📁 Dataset: [`lit2vec-tldr-bart-dataset`](https://huggingface.co/datasets/Bocklitz-Lab/lit2vec-tldr-bart-dataset)  
-- 💻 Code: [GitHub Repo](https://github.com/Bocklitz-Lab/lit2vec-tldr-bart)
+Lit2Vec TL;DR is an abstractive summarization tool for chemistry research abstracts, built using Gradio and a fine-tuned DistilBART model. It generates concise, structured summaries capturing the **methods**, **results**, and **significance** of scientific papers.
+🔬 Model: [`Bocklitz-Lab/lit2vec-tldr-bart-model`](https://huggingface.co/Bocklitz-Lab/lit2vec-tldr-bart-model)  
 
-Paste any chemistry abstract to get a TL;DR-style structured summary with just one click.