TigerBot: An Open Multilingual Multitask LLM
We release and introduce the TigerBot family of large language models (LLMs),
consisting of base and chat models, sized from 7, 13, 70 and 180 billion
parameters. We develop our models embarking from Llama-2 and BLOOM, and push
the boundary further in data, training algorithm, infrastructure, and
application tools. Our models yield meaningful performance gain over SOTA
open-source models, e.g., Llama-2, specifically 6\% gain in English and 20\%
gain in Chinese. TigerBot model family also achieves leading performance in
major academic and industrial benchmarks and leaderboards. We believe that
TigerBot represents just a snapshot of lightning-fast progression in LLM
open-source community. Therefore, we are thrilled to give back by publicly
releasing our models and reporting our approach behind, with additional
emphases on building SOTA LLMs in a democratized way and making LLMs of use in
real-world applications.
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Ye Chen
admin_assigned
2023-12-15T12:58:03.698Z
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Ye Chen
user
yechen
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Wei Cai
admin_assigned
2023-12-15T12:58:18.237Z
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WEI CAI
user
vivicai
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Liangmin Wu
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Xiaowei Li
657bc9b8b8d76880f8985990
Zhanxuan Xin
admin_assigned
2023-12-15T12:59:14.158Z
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xinzhanxuan
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xuangege
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Cong Fu
admin_assigned
2023-12-15T12:59:22.277Z
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cong fu
user
HetairoiF
TigerBot: An Open Multilingual Multitask LLM
We release and introduce the TigerBot family of large language models (LLMs),
consisting of base and chat models, sized from 7, 13, 70 and 180 billion
parameters. We develop our models embarking from Llama-2 and BLOOM, and push
the boundary further in data, training algorithm, infrastructure, and
application tools. Our models yield meaningful performance gain over SOTA
open-source models, e.g., Llama-2, specifically 6\% gain in English and 20\%
gain in Chinese. TigerBot model family also achieves leading performance in
major academic and industrial benchmarks and leaderboards. We believe that
TigerBot represents just a snapshot of lightning-fast progression in LLM
open-source community. Therefore, we are thrilled to give back by publicly
releasing our models and reporting our approach behind, with additional
emphases on building SOTA LLMs in a democratized way and making LLMs of use in
real-world applications.
TigerBot, a family of large language models, achieves superior performance over existing open-source models and benchmarks by advancing data, training algorithms, infrastructure, and application tools.
large language models LMMs Llama-2 BLOOM performance gain English Chinese academic benchmarks industrial leaderboards democratized way real-world applications