Update src/content.py

src/content.py

@@ -5,16 +5,23 @@ from .formatting import styled_warning
 # ================================
 INTRODUCTION_TITLE = """<h1 align="center">🏟️ Long Code Arena</h1>"""
 
-INTRODUCTION_TEXT = """🏟️ Long Code Arena is a benchmark of code-related tasks with large contexts, up to a whole code repository.
-It currently spans six different tasks.
+INTRODUCTION_TEXT = """🏟️ Long Code Arena is a suite of benchmarks for code-related tasks with large contexts, up to a whole code repository.
+It currently spans six different tasks and contains six datasets:
 
-We are excited to invite you to participate in our benchmark! To submit your results, please send the following materials to our 📩 email (lca@jetbrains.com):  
+* 🤗 [Library-based code generation](https://huggingface.co/datasets/JetBrains-Research/lca-library-based-code-generation)
+* 🤗 [CI builds repair](https://huggingface.co/datasets/JetBrains-Research/lca-ci-builds-repair)
+* 🤗 [Project-level code completion](https://huggingface.co/datasets/JetBrains-Research/lca-project-level-code-completion)
+* 🤗 [Commit message generation](https://huggingface.co/datasets/JetBrains-Research/lca-commit-message-generation)
+* 🤗 [Bug localization](https://huggingface.co/datasets/JetBrains-Research/lca-bug-localization)
+* 🤗 [Module summarization](https://huggingface.co/datasets/JetBrains-Research/lca-module-summarization)
+
+We are excited to invite you to participate in solving our benchmarks! To submit your results, please send the following materials to our 📩 email ([email protected]):  
 
 * Results: Include the summary of your benchmark outcomes.
-* Reproduction Package: To ensure the integrity and reproducibility of your results, please include the code for context collection (if any), predictions generation and evaluating. You can follow [our baselines code](https://github.com/JetBrains-Research/lca-baselines) as a reference.  
-* Metadata (model information, organization name, licence of your model, context size and other information you find relevant)
+* Reproduction Package: To ensure the integrity and reproducibility of your results, please include the code for context collection (if any), generation of predictions, and evaluating. You can follow [our baselines](https://github.com/JetBrains-Research/lca-baselines) as a reference.  
+* Metadata: Model information, organization name, licence of your model, context size, and other information you find relevant.
 
-We look forward to reviewing your innovative solutions.
+We look forward to reviewing your innovative solutions!
 
 """