#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
#CAKE/USDT analysis :
#CAKE has retraced and tapped the previous resistance zone, which is now support for the price. Bullish momentum is expected from the current level. Wait for the price to bounce back and break out of the $2.614 level to go long, with the previous swing high as the target level.
TF : 1D
Entry : $2.614
Target : $4.180
SL : $1.992
#CAKE/USDT analysis :
#CAKE is currently in an uptrend, forming higher highs (HHs) and higher lows (HLs) above the 200 Exponential Moving Average (200EMA). The price is anticipated to undergo a retracement and test a support zone before resuming its bullish momentum. A new high is likely to be established soon.
TF : 15min
Entry : $2.033
Target : $2.091
SL : $2.004