GWQ2b 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. GWQ2b models are well-suited for a variety of text generation tasks, including question answering, summarization, and reasoning. GWQ2b is fine-tuned on the Chain of Continuous Thought Synthetic Dataset, built upon the Gemma2forCasualLM architecture. You can ensure the correct chat template is applied by using tokenizer.applychattemplate as follows: 1. Transformer-Based Design: GWQ2b leverages the transformer architecture, utilizing self-attention mechanisms to process input text and capture contextual relationships effectively. 2. Lightweight and Efficient: It is designed to be computationally efficient, with fewer parameters compared to larger models, making it ideal for deployment on resource-constrained devices or environments. 3. Modular Layers: The architecture consists of modular encoder and decoder layers, allowing flexibility in adapting the model for specific…
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Автор: prithivMLmods
Теги: gemma2, gemma, 2b, CoT, text-generation-inference, gwq2b, gemma-with-question, conversational
Лайков: 3 | Загрузок: 34
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
