QuantFactory/LFM2-1.2B-RAG-GGUF

This is quantized version of LiquidAI/LFM2-1.2B-RAG created using llama.cpp Based on LFM2-1.2B, LFM2-1.2B-RAG is specialized in answering questions based on provided contextual documents, for use in RAG (Retrieval-Augmented Generation) systems. — Chatbot to ask questions about the documentation of a particular product. — Custom support with an internal knowledge base to provide grounded answers. — Academic research assistant with multi-turn conversations about research papers and course materials. You can find more information about other task-specific models in this blog post. Generation parameters: We recommend using greedy decoding with a temperature=0. System prompt: The system prompt is optional. You can force the output’s language, for example, using «Always respond in English, regardless of the user’s input language.» By default, the output’s language follows the user prompt’s language. Supported languages: English, Arabic, Chinese, French, German, Japanese, Korean, Portuguese, and Spanish. !68d417d4e3a23b976f25091aModel LibraryPrompt + Answer (Medium)_Lightmode Training approach: We fine-tuned the LFM2-1.2B-RAG model on a dataset that includes 1M+ samples of multi-turn…

Модальности:
Генерация текста

Задача: Генерация текста
Автор: QuantFactory
Теги: gguf, liquid, lfm2, edge, en, ar, zh, fr
Лайков: 3  |  Загрузок: 350

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