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  ---
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  language:
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- - en
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- - fr
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- - ro
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- - de
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- - multilingual
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- widget:
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- - text: 'Translate to German: My name is Arthur'
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- example_title: Translation
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- - text: >-
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- Please answer to the following question. Who is going to be the next
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- Ballon d'or?
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- example_title: Question Answering
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- - text: >-
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- Q: Can Geoffrey Hinton have a conversation with George Washington? Give
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- the rationale before answering.
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- example_title: Logical reasoning
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- - text: >-
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- Please answer the following question. What is the boiling point of
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- Nitrogen?
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- example_title: Scientific knowledge
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- - text: >-
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- Answer the following yes/no question. Can you write a whole Haiku in a
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- single tweet?
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- example_title: Yes/no question
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- - text: >-
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- Answer the following yes/no question by reasoning step-by-step. Can you
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- write a whole Haiku in a single tweet?
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- example_title: Reasoning task
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- - text: 'Q: ( False or not False or False ) is? A: Let''s think step by step'
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- example_title: Boolean Expressions
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- - text: >-
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- The square root of x is the cube root of y. What is y to the power of 2,
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- if x = 4?
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- example_title: Math reasoning
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- - text: >-
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- Premise: At my age you will probably have learnt one lesson. Hypothesis:
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- It's not certain how many lessons you'll learn by your thirties. Does the
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- premise entail the hypothesis?
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- example_title: Premise and hypothesis
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- - text: >-
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- Answer the following question by reasoning step by step.
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- The cafeteria had 23 apples. If they used 20 for lunch, and bought 6 more, how many apple do they have?
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- example_title: Chain of thought
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  tags:
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- - text2text-generation
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- - flan-ul2
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  datasets:
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- - svakulenk0/qrecc
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- - taskmaster2
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- - djaym7/wiki_dialog
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- - deepmind/code_contests
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- - lambada
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- - gsm8k
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- - aqua_rat
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- - esnli
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- - quasc
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- - qed
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- - c4
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- license: apache-2.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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@@ -244,4 +331,17 @@ This model was originally contributed by [Yi Tay](https://www.yitay.net/?author=
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  # Citation
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- If you want to cite this work, please consider citing the [blogpost](https://www.yitay.net/blog/flan-ul2-20b) announcing the release of `Flan-UL2`.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  language:
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+ - en
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+ - fr
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+ - ro
6
+ - de
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+ - multilingual
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+ license: apache-2.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  tags:
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+ - text2text-generation
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+ - flan-ul2
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  datasets:
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+ - svakulenk0/qrecc
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+ - taskmaster2
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+ - djaym7/wiki_dialog
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+ - deepmind/code_contests
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+ - lambada
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+ - gsm8k
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+ - aqua_rat
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+ - esnli
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+ - quasc
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+ - qed
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+ - c4
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+ widget:
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+ - text: 'Translate to German: My name is Arthur'
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+ example_title: Translation
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+ - text: Please answer to the following question. Who is going to be the next Ballon
28
+ d'or?
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+ example_title: Question Answering
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+ - text: 'Q: Can Geoffrey Hinton have a conversation with George Washington? Give the
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+ rationale before answering.'
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+ example_title: Logical reasoning
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+ - text: Please answer the following question. What is the boiling point of Nitrogen?
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+ example_title: Scientific knowledge
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+ - text: Answer the following yes/no question. Can you write a whole Haiku in a single
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+ tweet?
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+ example_title: Yes/no question
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+ - text: Answer the following yes/no question by reasoning step-by-step. Can you write
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+ a whole Haiku in a single tweet?
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+ example_title: Reasoning task
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+ - text: 'Q: ( False or not False or False ) is? A: Let''s think step by step'
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+ example_title: Boolean Expressions
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+ - text: The square root of x is the cube root of y. What is y to the power of 2, if
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+ x = 4?
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+ example_title: Math reasoning
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+ - text: 'Premise: At my age you will probably have learnt one lesson. Hypothesis: It''s
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+ not certain how many lessons you''ll learn by your thirties. Does the premise
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+ entail the hypothesis?'
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+ example_title: Premise and hypothesis
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+ - text: Answer the following question by reasoning step by step. The cafeteria had
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+ 23 apples. If they used 20 for lunch, and bought 6 more, how many apple do they
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+ have?
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+ example_title: Chain of thought
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+ model-index:
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+ - name: flan-ul2
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+ results:
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: IFEval (0-Shot)
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+ type: HuggingFaceH4/ifeval
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: inst_level_strict_acc and prompt_level_strict_acc
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+ value: 23.93
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+ name: strict accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=google/flan-ul2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: BBH (3-Shot)
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+ type: BBH
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+ args:
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+ num_few_shot: 3
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+ metrics:
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+ - type: acc_norm
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+ value: 30.02
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+ name: normalized accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=google/flan-ul2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MATH Lvl 5 (4-Shot)
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+ type: hendrycks/competition_math
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+ args:
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+ num_few_shot: 4
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+ metrics:
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+ - type: exact_match
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+ value: 0.15
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+ name: exact match
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=google/flan-ul2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: GPQA (0-shot)
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+ type: Idavidrein/gpqa
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: acc_norm
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+ value: 5.03
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+ name: acc_norm
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=google/flan-ul2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MuSR (0-shot)
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+ type: TAUR-Lab/MuSR
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: acc_norm
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+ value: 5.58
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+ name: acc_norm
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=google/flan-ul2
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+ name: Open LLM Leaderboard
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+ - task:
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+ type: text-generation
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+ name: Text Generation
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+ dataset:
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+ name: MMLU-PRO (5-shot)
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+ type: TIGER-Lab/MMLU-Pro
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+ config: main
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+ split: test
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+ args:
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+ num_few_shot: 5
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+ metrics:
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+ - type: acc
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+ value: 16.59
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=google/flan-ul2
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+ name: Open LLM Leaderboard
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  ---
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  # Citation
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+ If you want to cite this work, please consider citing the [blogpost](https://www.yitay.net/blog/flan-ul2-20b) announcing the release of `Flan-UL2`.
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+ # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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+ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_google__flan-ul2)
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+
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+ | Metric |Value|
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+ |-------------------|----:|
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+ |Avg. |13.55|
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+ |IFEval (0-Shot) |23.93|
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+ |BBH (3-Shot) |30.02|
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+ |MATH Lvl 5 (4-Shot)| 0.15|
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+ |GPQA (0-shot) | 5.03|
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+ |MuSR (0-shot) | 5.58|
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+ |MMLU-PRO (5-shot) |16.59|
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+