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Source channel @githubtrending · Post #14909 · Jul 3
#other#agent#llm#rag Happy-LLM is a free, open-source learning project that helps you deeply understand large language models (LLMs) from basics to advanced training and applications. It teaches you key concepts like NLP, Transformer architecture, pretraining, and how to build and train your own LLaMA2 model step-by-step. You also learn practical skills like fine-tuning and using cutting-edge techniques such as Retrieval-Augmented Generation (RAG) and intelligent agents. This project is ideal if you know some Python and deep learning, and it offers both theory and hands-on code to help you master LLM development and apply it in real-world AI tasks. This can boost your skills and confidence in AI model building and research. https://github.com/datawhalechina/happy-llm
Search: #l1
@ethereumglobalnews · Post #1454 · 12/01/2025, 06:57 AM
🪙 Vitalik: “You can just build on #L1” as fees stay cheap in 2025. #ETH 😎 Vitalik 表示: 由於 2025 年以太坊交易費持續保持低位，「直接在 L1 上構建」依然可行。今年以來 L1 需求增速溫和、區塊空間壓力未現顯著擁堵。 #Ethereum#DeFi#以太坊#市場趨勢 ——— ⚡️ 若費用長期維持低檔，L1 與 Rollup 的功能分工可能再度被市場重估 #Scaling ✅Chat: @Web3NewsInsight 🦂 👇Tip👇讚 或點擊進行💎資源搜索👇
@ethereumglobalnews · Post #1618 · 12/26/2025, 04:57 AM
🪙 L1 Tokens 2025 Performance Castle Labs data shows most Layer 1 tokens ended 2025 in negative territory. Only BNB (+18.2%) and TRX (+9.8%) managed to stay in positive returns. • ETH：-15.3% • SOL：-35.9% • SUI / AVAX：跌幅均超 -67% • TON：全年回撤接近 -74% ⚡️ 結構性行情下L1 不再齊漲齊跌 #Ethereum#L1#CryptoMarkets #OnChain#BNB#以太坊 —————— 👇⭐️👇 🤣 🥲👇 資源搜索 🖲️👆
@deep_school · Post #83 · 09/20/2022, 02:35 PM
Сегодня вторник, а значит в эфире рубрика “повторяем теорию”🤓 Вспомним про регуляризацию сетей, а именно про три популярных метода: L1, L2 и Dropout (ведь был популярен когда-то, надо отдать дань старичку). Статья в телеграфе 👉Регуляризуем правильно! #регуляризация#L1#L2#dropout
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