#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
#XTZ/USDT analysis :
#XTZ is in an uptrend and has broken out above the 200 EMA and previous highs. Currently, the price is retesting the previous resistance zone, which has now turned into support. It is anticipated that the price will rebound from this level and resume bullish momentum to test the previous highs.
TF : 1D
Entry : $1.012
Target : $1.800
SL : $0.783
#XTZ/USDT analysis :
#XTZ has broken below the 200 EMA and has retested it. Currently, the price is encountering resistance from the resistance zone, and it is expected to decline from here. A drop is anticipated, potentially leading to a test of previous lows.
TF : 2H
Entry : $1.420
Target : $1.150
SL : $1.530
#XTZ/USDT analysis :
#XTZ has broken out and retested the previous swing high and the 200 EMA. The price is expected to bounce back from this level and test the higher levels.
TF : 4H
Entry : $0.694
Target : $0.744
SL : $0.661
#XTZ/USDT analysis :
#XTZ is again approaching the 200 EMA resistance after facing rejection from there and is expected to continue its bearish momentum once the zone is tested. The previous low will be the target level.
TF : 2H
Entry : $0.687
Target : $0.591
SL : $0.709