#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag
Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data.
https://github.com/FareedKhan-dev/all-rag-techniques
#ICP/USDT analysis :
#ICP is currently developing a symmetrical triangle pattern on the higher time frame (HTF). A breakout above the resistance level of $10.230 is anticipated, which could signal the continuation of a bullish rally. For a confirmed entry, it is advisable to wait for the price to surpass this resistance level.
TF : 1W
Entry : $10.230
Target : $20.500
SL : $7.760
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