models(gallery): add gemma2-9b-it and gemma2-27b-it (#2670)

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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Ettore Di Giacinto 2024-06-27 23:08:22 +02:00 committed by GitHub
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@ -312,6 +312,34 @@
- filename: gemma-1.1-7b-it-Q4_K_M.gguf
sha256: 47821da72ee9e80b6fd43c6190ad751b485fb61fa5664590f7a73246bcd8332e
uri: huggingface://bartowski/gemma-1.1-7b-it-GGUF/gemma-1.1-7b-it-Q4_K_M.gguf
- !!merge <<: *gemma
name: "gemma-2-27b-it"
urls:
- https://huggingface.co/google/gemma-2-27b-it
- https://huggingface.co/bartowski/gemma-2-27b-it-GGUF
description: |
Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. They are text-to-text, decoder-only large language models, available in English, with open weights for both pre-trained variants and instruction-tuned variants. Gemma models are well-suited for a variety of text generation tasks, including question answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as a laptop, desktop or your own cloud infrastructure, democratizing access to state of the art AI models and helping foster innovation for everyone.
overrides:
parameters:
model: gemma-2-27b-it-Q4_K_M.gguf
files:
- filename: gemma-2-27b-it-Q4_K_M.gguf
sha256: e54e7b800d464af4fa9966020e4a1b1d386cd9346de2d851a7bfe7d0797c44c4
uri: huggingface://bartowski/gemma-2-27b-it-GGUF/gemma-2-27b-it-Q4_K_M.gguf
- !!merge <<: *gemma
name: "gemma-2-9b-it"
urls:
- https://huggingface.co/google/gemma-2-9b-it
- https://huggingface.co/bartowski/gemma-2-9b-it-GGUF
description: |
Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. They are text-to-text, decoder-only large language models, available in English, with open weights for both pre-trained variants and instruction-tuned variants. Gemma models are well-suited for a variety of text generation tasks, including question answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as a laptop, desktop or your own cloud infrastructure, democratizing access to state of the art AI models and helping foster innovation for everyone.
overrides:
parameters:
model: gemma-2-9b-it-Q4_K_M.gguf
files:
- filename: gemma-2-9b-it-Q4_K_M.gguf
sha256: 0874bf61be2e4b3d0a4a75e58fbd442dc410745d513c1e1e5de0b54ae33e65db
uri: huggingface://bartowski/gemma-2-9b-it-GGUF/gemma-2-9b-it-Q4_K_M.gguf
- &llama3
url: "github:mudler/LocalAI/gallery/llama3-instruct.yaml@master"
icon: https://cdn-uploads.huggingface.co/production/uploads/642cc1c253e76b4c2286c58e/aJJxKus1wP5N-euvHEUq7.png