Sfarzi commited on
Commit
5dd5fd1
·
1 Parent(s): 2c897f3

Initial clone with modifications

Browse files
Files changed (1) hide show
  1. src/about.py +1 -1
src/about.py CHANGED
@@ -112,7 +112,7 @@ TITLE = """<h1 align="center" id="space-title">🚀 ECREAM-LLM Leaderboard 🚀<
112
 
113
  # What does your leaderboard evaluate?
114
  INTRODUCTION_TEXT = """
115
- <br><br><b>The eCream-LLM leaderboard </b>, developed within the eCream Project (enabling Clinical Research in Emergency and Acute care Medicine), is designed to evaluate Large Language Models (LLMs) on two tasks pertaining to the medical domain. Its distinguishing features are:<b> <br> (i) all tasks are implemented for six languages including English, Italian, Slovak, Slovenian, Polish and Greek; <br> (ii) all tasks are generative, thus allowing for a more natural interaction with LLMs; <br> (iii) all tasks are evaluated against multiple prompts, this way mitigating the model sensitivity to specific prompts and allowing a fairer evaluation.</b>
116
  <br><br>**<small>Generative tasks:</small>** <small> 🏷️NER (Named Entity Recognition), 🔗REL (Relation Extraction) </small>
117
  """
118
  ##**<small>Multiple-choice tasks:</small>** <small> 📊TE (Textual Entailment), 😃SA (Sentiment Analysis), ⚠️HS (Hate Speech Detection), 🏥AT (Admission Test), 🔤WIC (Word in Context), ❓FAQ (Frequently Asked Questions) </small><br>
 
112
 
113
  # What does your leaderboard evaluate?
114
  INTRODUCTION_TEXT = """
115
+ <br><br><b>The eCream-LLM leaderboard </b>, developed within <a href='https://ecreamproject.eu/'> the eCream Project </a> (enabling Clinical Research in Emergency and Acute care Medicine), is designed to evaluate Large Language Models (LLMs) on two tasks pertaining to the medical domain. Its distinguishing features are:<b> <br> (i) all tasks are implemented for six languages including English, Italian, Slovak, Slovenian, Polish and Greek; <br> (ii) all tasks are generative, thus allowing for a more natural interaction with LLMs; <br> (iii) all tasks are evaluated against multiple prompts, this way mitigating the model sensitivity to specific prompts and allowing a fairer evaluation.</b>
116
  <br><br>**<small>Generative tasks:</small>** <small> 🏷️NER (Named Entity Recognition), 🔗REL (Relation Extraction) </small>
117
  """
118
  ##**<small>Multiple-choice tasks:</small>** <small> 📊TE (Textual Entailment), 😃SA (Sentiment Analysis), ⚠️HS (Hate Speech Detection), 🏥AT (Admission Test), 🔤WIC (Word in Context), ❓FAQ (Frequently Asked Questions) </small><br>