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Source channel @githubtrending · Post #14993 · Jul 24

#jupyter_notebook 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

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@signal_bitcoins · Post #1883 · 12/17/2023, 07:38 AM

💰#WAVES is trying to break up the triangle pattern on Weekly Time frame,in the case of breakout we will have another good pump💎 ❄️@signals_bitcoin_crypto❄️ ❄️@Shadow_support0o❄️

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@signal_bitcoins · Post #1468 · 09/09/2023, 09:00 PM

💰#WAVES is moving in a descending triangle. It bounced from the horizontal support with a decent volume. Currently, it is facing the MA 50 resistance. MACD crossover is losing bearish momentum and seems like it is going to turn bullish. A solid breakout of the descending triangle would be the bullish confirmation.💎 ❄️@signals_bitcoin_crypto❄️ ❄️@Shadow_support0o❄️

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