#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
#ALPINE/USDT analysis :
#ALPINE is currently in a downtrend, trading below the 200 Exponential Moving Average (EMA) and making new lows. The price is expected to continue its bearish momentum and test lower levels. For a short entry, wait for the price to test the zone and resume its bearish momentum.
TF : 4H
Entry : $0.923
Target : $0.819
SL : $0.991
#ALPINE/USDT analysis :
#ALPINE is in a downtrend, trading below the 200 EMA. The price is currently facing rejection from the resistance zone and is expected to continue its downward movement. look for retracement to enter short positions.
TF : 4H
Entry : $1.094
Target : $0.917
SL : $1.202
#ALPINE/USDT analysis -
#ALPINE is in a downtrend. It is currently experiencing a pullback while finding support over the trendline. Wait for the price to break the trendline for a short entry as the price is expected to face resistance from the 200 EMA and continue its bearish momentum.
TF : 1H
Entry : $1.055
Target : $0.927
SL : $1.124