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Human evaluation of Mistral 7B – Instruct vs Llama 2 13B – Chat Example

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Human evaluation of Mistral 7B – Instruct vs Llama 2 13B – Chat Example has 8 facts recorded in Dontopedia across 3 references, with 2 live disagreements.

8 facts·4 predicates·3 sources·2 in dispute

Mostly:rdf:type(3), compares(2), conducted on(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (2)

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basedOnBased on(1)

mentionsMethodMentions Method(1)

Other facts (7)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

7 facts
PredicateValueRef
Rdf:typeEvaluation Method[1]
Rdf:typeEvaluation Method[2]
Rdf:typeFigure[3]
ComparesMistral 7b Instruct[3]
ComparesLlama 2 13b Chat[3]
Conducted onLeaderboard[3]
SourceLlmboxing Com[3]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

typebeam/5fac4cc5-62c6-4b3f-9064-15f4806ba3b5
ex:EvaluationMethod
typebeam/8563ca84-0d37-48e4-9de6-fd9401a1de41
ex:Evaluation_Method
conductedOndocument/013ce683-54a9-49ec-a919-ea7a77edb6f6
https://llmboxing.com/leaderboard
typedocument/013ce683-54a9-49ec-a919-ea7a77edb6f6
ex:Figure
labeldocument/013ce683-54a9-49ec-a919-ea7a77edb6f6
Human evaluation of Mistral 7B – Instruct vs Llama 2 13B – Chat Example
sourcedocument/013ce683-54a9-49ec-a919-ea7a77edb6f6
ex:llmboxing-com
comparesdocument/013ce683-54a9-49ec-a919-ea7a77edb6f6
ex:mistral-7b-instruct
comparesdocument/013ce683-54a9-49ec-a919-ea7a77edb6f6
ex:llama-2-13b-chat

References (3)

3 references
  1. ctx:claims/beam/5fac4cc5-62c6-4b3f-9064-15f4806ba3b5
    • full textbeam-chunk
      text/plain1 KBdoc:beam/5fac4cc5-62c6-4b3f-9064-15f4806ba3b5
      Show excerpt
      [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [9, 10, 11, 12, 13, 14, 15, 16, 17, 18], [17, 18, 19, 20]] ``` ### Additional Considerations 1. **Tokenization**: - If your input data is text, ensure that you tokenize it appropriately before segmenti
  2. ctx:claims/beam/8563ca84-0d37-48e4-9de6-fd9401a1de41
    • full textbeam-chunk
      text/plain1 KBdoc:beam/8563ca84-0d37-48e4-9de6-fd9401a1de41
      Show excerpt
      By implementing these optimizations, you should be able to reduce the processing time and improve the performance of your spelling correction module. [Turn 10240] User: I'm working on a project to improve the search accuracy of our RAG sys
  3. ctx:claims/document/013ce683-54a9-49ec-a919-ea7a77edb6f6
    • full textmistral7b.txt
      text/plain24 KBdonto:blob/sha256/a1ee205dee010ebc8a172066f2792e57b67f168f495aed1deef4f7f99b144731
      Show excerpt
      Mistral 7B arXiv:2310.06825v1 [cs.CL] 10 Oct 2023 Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Léli

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