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Retrieval Augmented Generation (RAG) helps large language models (LLMs) answer questions using up-to-date or private information by connecting them to external data sources, unlike fine-tuning which retrains the model on specific data. RAG is useful when you need current, dynamic information without costly retraining, making it ideal for tasks like customer support or knowledge management. Fine-tuning is better for deep expertise in a specialized field but requires more data and effort. Using RAG lets you get accurate, relevant answers quickly by combining the model’s language skills with fresh, specific data, improving usefulness and reliability.
https://github.com/langchain-ai/rag-from-scratch
希希well🏠#zz
兼职|来自浙江的女孩
温柔气质女友大四实习生纯天然无整容
干净而纯粹的白·简单又纯净
无纹身 不抽烟
There is more to come.
·Age年龄: 03年
·Weight体重:45kg
·Height身高: 176cm
·Bust胸围: C-cup
就读于山东省《曲阜师范大学》 A4腰·纤长细腿·黄金比例温柔·清纯·高级·气质温婉
You are my today and all of my tomorrows.
一个心中有梦 眼里有光的女孩
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