Tesslate/Synthia-S1-27b
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Tris Warkentin
trisfromgoogle
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Very excited to share the first two official Gemma variants from Google! Today at Google Cloud Next, we announced cutting-edge models for code and research!
First, google/codegemma-release-66152ac7b683e2667abdee11 - a new set of code-focused Gemma models at 2B and 7B, in both pretrained and instruction-tuned variants. These exhibit outstanding performance on academic benchmarks and (in my experience) real-life usage. Read more in the excellent HuggingFace blog: https://huggingface.co/blog/codegemma
Second, ( google/recurrentgemma-release-66152cbdd2d6619cb1665b7a), which is based on the outstanding Google DeepMind research in Griffin: https://arxiv.org/abs/2402.19427. RecurrentGemma is a research variant that enables higher throughput and vastly improved memory usage. We are excited about new architectures, especially in the lightweight Gemma sizes, where innovations like RecurrentGemma can scale modern AI to many more use cases.
For details on the launches of these models, check out our launch blog -- and please do not hesitate to send us feedback. We are excited to see what you build with CodeGemma and RecurrentGemma!
Huge thanks to the Hugging Face team for helping ensure that these models work flawlessly in the Hugging Face ecosystem at launch!
First, google/codegemma-release-66152ac7b683e2667abdee11 - a new set of code-focused Gemma models at 2B and 7B, in both pretrained and instruction-tuned variants. These exhibit outstanding performance on academic benchmarks and (in my experience) real-life usage. Read more in the excellent HuggingFace blog: https://huggingface.co/blog/codegemma
Second, ( google/recurrentgemma-release-66152cbdd2d6619cb1665b7a), which is based on the outstanding Google DeepMind research in Griffin: https://arxiv.org/abs/2402.19427. RecurrentGemma is a research variant that enables higher throughput and vastly improved memory usage. We are excited about new architectures, especially in the lightweight Gemma sizes, where innovations like RecurrentGemma can scale modern AI to many more use cases.
For details on the launches of these models, check out our launch blog -- and please do not hesitate to send us feedback. We are excited to see what you build with CodeGemma and RecurrentGemma!
Huge thanks to the Hugging Face team for helping ensure that these models work flawlessly in the Hugging Face ecosystem at launch!
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🎉 Super
@DeepMount00
just released 𝗚𝗲𝗺𝗺𝗮_𝗤𝗔_𝗜𝗧𝗔_𝘃𝟯 𝗹𝗲𝗮𝗱𝗶𝗻𝗴 the 𝗥𝗔𝗚 𝘁𝗮𝘀𝗸 on the Italian 𝗟𝗟𝗠_𝗜𝗧𝗔_𝗟𝗘𝗔𝗗𝗘𝗥𝗕𝗢𝗔𝗥𝗗. The model is a fine tuned version of Gemma 2B.
Model details: https://huggingface.co/DeepMount00/Gemma_QA_ITA_v3
Explore the full RAG section rankings here: https://huggingface.co/spaces/FinancialSupport/open_ita_llm_leaderboard on section Classifica RAG
Model details: https://huggingface.co/DeepMount00/Gemma_QA_ITA_v3
Explore the full RAG section rankings here: https://huggingface.co/spaces/FinancialSupport/open_ita_llm_leaderboard on section Classifica RAG
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Proposal for Renaming of Gemma-7B Model to Gemma-9B
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#34 opened about 1 year ago
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Is this the same as Gemini Nano?
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#25 opened about 1 year ago
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7B or 8B?
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#24 opened about 1 year ago
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New base pretrained models on the Open LLM Leaderboard!
Two new OSS models by Google, who's getting back in the game 😎
The 7B is 2nd of the leaderboard, and better than Mistral (notably on GSM8K, aka math).
google/gemma-7b
google/gemma-2b
Check more results on the leaderboard https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
Two new OSS models by Google, who's getting back in the game 😎
The 7B is 2nd of the leaderboard, and better than Mistral (notably on GSM8K, aka math).
google/gemma-7b
google/gemma-2b
Check more results on the leaderboard https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard