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Source channel @githubtrending · Post #14993 · Jul 24
#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
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@proanalysistrader · Post #28408 · 01/21/2025, 02:58 PM
#FIRO/USDT analysis : #FIRO is in an uptrend, trading above the 200 EMA. The price has retraced and tested the support zone. It is currently bouncing back from this zone, with expectations to resume bullish momentum and test the previous swing high. TF : 1D Entry : $1.850 Target : $2.840 SL : $1.367
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@americancryptotrading · Post #27102 · 12/30/2024, 03:08 PM
🇺🇸#FIRO/USDT is trading above the fallingwedge formation on the weekly timeframe🔥 Pump is expected🚀 American Crypto©
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@coinlegs · Post #10136 · 03/26/2024, 10:48 PM
📗Trend Line Touch Binance / 26 Mar 22:00 / 1h #FIRO : 2.125
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@coinlegs · Post #9696 · 01/09/2024, 06:21 AM
🐬DOLPHIN | AI PREDICTIONS 09.01.2024 06:00 GMT Expected 5% Profit/Loss in 24 Hours #NFP | 0.58321 | PP: 92% | LP: 9% #FIRO | 1.585 | PP: 90% | LP: 0% #GFT | 0.02027 | PP: 87% | LP: 100% #JTO | 1.7112 | PP: 86% | LP: 100% #NTRN | 1.5177 | PP: 78% | LP: 100% #ORDI | 74.726 | PP: 77% | LP: 100% #TIA | 15.578 | PP: 77% | LP: 100% #VANRY | 0.05837 | PP: 74% | LP: 96% #IQ | 0.00531 | PP: 66% | LP: 100% #MEME | 0.023135 | PP: 64% | LP: 90% #ACE | 8.2438 | PP: 28% | LP: 91% #ARK | 0.7136 | PP: 23% | LP: 91% ——————————————————————— Total Predictions: 366 PP > 50%: 328 LP > 50%: 18 PP > 60%: 202 LP > 60%: 17 PP > 70%: 54 LP > 70%: 16 PP > 80%: 36 LP > 80%: 16 PP > 90%: 1 LP > 90%: 9 ——————————————————————— PP: Profit Probability | LP: Loss Probability