#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
#ADX/USDT analysis :
#ADX is currently in a downtrend and trading below its 200 exponential moving average (EMA). The price is encountering resistance from the 200 EMA and a resistance zone. It is anticipated that the price will decline from this point and test lower levels.
TF : 2h
Entry : $0.1090
Target : $0.0963
SL : $0.1173
#ADX/USDT analysis :
#ADX is currently in an uptrend, making new highs while trading above the 200 EMA and the support zone. The price is anticipated to resume its bullish momentum and test the previous swing high. Look for a pullback for a long entry.
TF : 4H
Entry : $0.1659
Target : $0.1934
SL : $0.1550
#ADX profit projections if remains in bull zone
Strong support Layer
220-225
Above this value #ADX will remain in bull Zone and will go as projected 🚀🚀