Find similar content

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

Hashtags

#jupyter_notebook

Results

1 similar post found

Search: #blockdiscovery

当前筛选 #blockdiscovery清除筛选

Crypto M - Crypto News

@CryptoM · Post #64625 · 04/09/2026, 11:54 AM

Find similar View

🚀 Independent Miner Achieves Rare Bitcoin Block Discovery An independent Bitcoin miner achieved a rare feat by successfully mining a Bitcoin block with a very low probability. According to BlockBeats, the miner used CKpool's solo mining software to mine block number 944,306, earning a total of 3.128 Bitcoin. Data from block explorer Mempool indicates that the miner received a block subsidy of 3.125 Bitcoin and transaction fees amounting to 0.003 Bitcoin. CKpool developer Con Kolivas noted on the X platform that the miner accomplished this with just 70TH of computing power. The probability of a miner of this scale discovering a block daily is approximately one in 100,000, with an average occurrence of once every 300 years. #Bitcoin#mining#CKpool#blockchain#rarefeat#blockdiscovery#cryptocurrency#soloMining#Mempool#transactionfees#ConKolivas#BTC

Hashtags

#bitcoin #mining #ckpool #blockchain #rarefeat #blockdiscovery #cryptocurrency #solomining #mempool #transactionfees #conkolivas #btc