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Update src/display/about.py

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Add a brief description of the task and dataset and a link to the blog post in the intro text

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  1. src/display/about.py +4 -0
src/display/about.py CHANGED
@@ -5,6 +5,10 @@ TITLE = """<h1 align="center" id="space-title">Hallucinations Leaderboard</h1>""
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  INTRODUCTION_TEXT = """
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  πŸ“ The Hallucinations Leaderboard aims to track, rank and evaluate hallucinations in LLMs.
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  Submit a model for automated evaluation on the [Edinburgh International Data Facility](https://www.epcc.ed.ac.uk/hpc-services/edinburgh-international-data-facility) (EIDF) GPU cluster on the "Submit" page.
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  The leaderboard's backend runs the great [Eleuther AI Language Model Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) - more details in the "About" page.
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  """
 
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  INTRODUCTION_TEXT = """
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  πŸ“ The Hallucinations Leaderboard aims to track, rank and evaluate hallucinations in LLMs.
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+ It evaluates the propensity for hallucination in Large Language Models (LLMs) across a diverse array of tasks, including Closed-book Open-domain QA, Summarization, Reading Comprehension, Instruction Following, Fact-Checking, Hallucination Detection, and Self-Consistency. The evaluation encompasses a wide range of datasets such as NQ Open, TriviaQA, TruthfulQA, XSum, CNN/DM, RACE, SQuADv2, MemoTrap, IFEval, FEVER, FaithDial, True-False, HaluEval, and SelfCheckGPT, offering a comprehensive assessment of each model's performance in generating accurate and contextually relevant content.
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+
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+ A more detailed explanation of the definition of hallucination and the leaderboard's motivation, tasks and dataset can be found on the "About" page and [The Hallucinations Leaderboard blog post](https://huggingface.co/blog/leaderboards-on-the-hub-hallucinations).
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+
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  Submit a model for automated evaluation on the [Edinburgh International Data Facility](https://www.epcc.ed.ac.uk/hpc-services/edinburgh-international-data-facility) (EIDF) GPU cluster on the "Submit" page.
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  The leaderboard's backend runs the great [Eleuther AI Language Model Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) - more details in the "About" page.
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  """