Update README.md

README.md

@@ -1,6 +1,6 @@
 ---
 title: LeaderboardFinder
-emoji: 🐢
+emoji: 🔎
 colorFrom: pink
 colorTo: gray
 sdk: gradio
@@ -9,50 +9,4 @@ app_file: app.py
 pinned: false
 ---
 
-If you want your leaderboard to appear, feel free to add relevant information in its metadata, and it will be displayed here.
-
-# Categories
-
-## Submission type
-Arenas are not concerned by this category.
-
-- `submission:automatic`: users can submit their models as such to the leaderboard, and evaluation is run automatically without human intervention
-- `submission:semiautomatic`: the leaderboard requires the model owner to run evaluations on his side and submit the results
-- `submission:manual`: the leaderboard requires the leaderboard owner to run evaluations for new submissions
-- `submission:closed`: the leaderboard does not accept submissions at the moment
-
-## Test set status
-Arenas are not concerned by this category.
-
-- `test:public`: all the test sets used are public, the evaluations are completely reproducible
-- `test:mix`: some test sets are public and some private
-- `test:private`: all the test sets used are private, the evaluations are hard to game
-- `test:rolling`: the test sets used change regularly through time and evaluation scores are refreshed
-
-## Judges
-- `judge:auto`: evaluations are run automatically, using an evaluation suite such as `lm_eval` or `lighteval`
-- `judge:model`: evaluations are run using a model as a judge approach to rate answer
-- `judge:humans`: evaluations are done by humans to rate answer - this is an arena
-- `judge:vibe_check`: evaluations are done manually by one human
-
-## Modalities
-Can be any (or several) of the following list:
-- `modality:text`
-- `modality:image`
-- `modality:video`
-- `modality:audio`
-A bit outside of usual modalities
-- `modality:tools`: requires added tool usage - mostly for assistant models
-- `modality:artefacts`: the leaderboard concerns itself with machine learning artefacts as themselves, for example, quality evaluation of text embeddings.
-
-## Evaluation categories
-Can be any (or several) of the following list:
-- `eval:generation`: the evaluation looks at generation capabilities specifically (can be image generation, text generation, ...) 
-- `eval:math`
-- `eval:code`
-- `eval:performance`: model performance (speed, energy consumption, ...)
-- `eval:safety`: safety, toxicity, bias evaluations
-
-## Language
-You can indicate the languages covered by your benchmark like so: `language:mylanguage`. 
-At the moment, we do not support language codes, please use the language name in English.
+If you want your leaderboard to appear, feel free to add relevant information in its metadata, and it will be displayed here (see the About tab).