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  ![gwq2.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/Ayc6YKE6FKYKb8Mible4z.png)
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- # **GWQ-9B-Preview2**
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  GWQ2 - Gemma with Questions Prev is a family of lightweight, state-of-the-art open models from Google, built using the same research and technology employed to create the Gemini models. These models are text-to-text, decoder-only large language models, available in English, with open weights for both pre-trained and instruction-tuned variants. Gemma models are well-suited for a variety of text generation tasks, including question answering, summarization, and reasoning. GWQ is fine-tuned on the Chain of Continuous Thought Synthetic Dataset, built upon the Gemma2forCasualLM architecture.
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  ![gwq2.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/Ayc6YKE6FKYKb8Mible4z.png)
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+ # **GWQ-9B-Preview 1&2 GGUF**
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  GWQ2 - Gemma with Questions Prev is a family of lightweight, state-of-the-art open models from Google, built using the same research and technology employed to create the Gemini models. These models are text-to-text, decoder-only large language models, available in English, with open weights for both pre-trained and instruction-tuned variants. Gemma models are well-suited for a variety of text generation tasks, including question answering, summarization, and reasoning. GWQ is fine-tuned on the Chain of Continuous Thought Synthetic Dataset, built upon the Gemma2forCasualLM architecture.
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