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README.md
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1. Superior performance in its class: Bielik-11B-v2.3-Instruct outperforms all other models with less than 70B parameters. This is a significant achievement, showcasing its efficiency and effectiveness despite having fewer parameters than many competitors.
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2. Competitive with larger models: with a score of
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3. Substantial improvement over previous version: the model shows a marked improvement over its predecessor, Bielik-7B-Instruct-v0.1, which scored 43.64. This leap in performance highlights the successful enhancements and optimizations implemented in this newer version.
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| Bielik-11B-v2.0-Instruct | 11 | 65.58 |
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| gpt-3.5-turbo-instruct | Unknown | 55.65 |
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The performance variation among Bielik versions is minimal, indicating consistent quality across iterations. Bielik-11B-v2.3-Instruct demonstrates an impressive
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### Open LLM Leaderboard
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1. Superior performance in its class: Bielik-11B-v2.3-Instruct outperforms all other models with less than 70B parameters. This is a significant achievement, showcasing its efficiency and effectiveness despite having fewer parameters than many competitors.
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2. Competitive with larger models: with a score of 65.71, Bielik-11B-v2.3-Instruct performs on par with models in the 70B parameter range. This indicates that it achieves comparable results to much larger models, demonstrating its advanced architecture and training methodology.
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3. Substantial improvement over previous version: the model shows a marked improvement over its predecessor, Bielik-7B-Instruct-v0.1, which scored 43.64. This leap in performance highlights the successful enhancements and optimizations implemented in this newer version.
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| Bielik-11B-v2.0-Instruct | 11 | 65.58 |
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| gpt-3.5-turbo-instruct | Unknown | 55.65 |
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The performance variation among Bielik versions is minimal, indicating consistent quality across iterations. Bielik-11B-v2.3-Instruct demonstrates an impressive 21.2% performance advantage over GPT-3.5.
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### Open LLM Leaderboard
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