#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
#MBL/USDT analysis :
#MBL is currently consolidating above the support zone. The price is expected to test this zone again before moving towards the swing high. It is recommended to wait for a pullback to enter a long position.
TF : 1D
Entry : $0.002672
Target : $0.003095
SL : $0.002527
#MBL/USDT analysis :
#MBL is in an uptrend, forming higher highs (HHs) and higher lows (HLs) above the 200 EMA. The price has recently bounced back from a support zone after retracement to it. It is expected that the price will sustain its bullish momentum and test the previous swing high.
TF : 1H
Entry : $0.00256
Target : $0.00265
SL : $0.00251
#MBL/USDT analysis :
#MBL is in a downtrend, trading below the 200 EMA. The price is expected to experience a pullback and will continue its downward momentum. Wait for the price to reject from the resistance zone for short entry.
TF : 15min
Entry : $0.00211
Target : $0.00190
SL : $0.00220
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