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Introduce EAGLE, a new method for fast LLM decoding based on compression: - 3x🚀than vanilla - 2x🚀 than Lookahead (on its benchmark) - 1.6x🚀 than Medusa (on its benchmark) - provably maintains text distribution - trainable (in 1~2 days) and testable on RTX 3090s Playground: Blog: Code: ⚒️First Principle:...

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Hongyang Zhang

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118,810 görüntüleme • 2 yıl önce •via X (Twitter)

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Jointly announcing EAGLE-3 with SGLang: Setting a new record in LLM inference acceleration! - 5x🚀than vanilla (on HF) - 1.4x🚀than EAGLE-2 (on HF) - A record of ~400 TPS on LLama 3.1 8B with a single H100 (on SGLang) - 1.65x🚀in latency even for large bs=64 (on SGLang) - A new scaling law: more training data, better speedup - Apache 2.0 Paper: Code: SGLang version: ⚒️Takeaway: Introducing training-time test, a novel draft model training technique: we replace feature prediction with direct token prediction and shift from top-layer-only features to multi-layer feature fusion. This approach unlocks a new scaling law previously undiscovered in EAGLE and EAGLE-2. 🙏Acknowledge: We would like to thank the SGLang team (zhyncs Lianmin Zheng Ying Sheng James Liu, Ke Bao, and others LMSYS Org) for their merge and careful evaluation of EAGLE-3 on SGLang. 🤝Want to collaborate? We're a small academic group with limited GPU resources. If you're interested in supporting our next version of EAGLE or would like us to train a preliminary version tailored to a specific model, please get in touch! Joint work with Yuhui Li, Fangyun Wei, and Chao Zhang
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Jointly announcing EAGLE-3 with SGLang: Setting a new record in LLM inference acceleration! - 5x🚀than vanilla (on HF) - 1.4x🚀than EAGLE-2 (on HF) - A record of ~400 TPS on LLama 3.1 8B with a single H100 (on SGLang) - 1.65x🚀in latency even for large bs=64 (on SGLang) - A new scaling law: more training data, better speedup - Apache 2.0 Paper: Code: SGLang version: ⚒️Takeaway: Introducing training-time test, a novel draft model training technique: we replace feature prediction with direct token prediction and shift from top-layer-only features to multi-layer feature fusion. This approach unlocks a new scaling law previously undiscovered in EAGLE and EAGLE-2. 🙏Acknowledge: We would like to thank the SGLang team (zhyncs Lianmin Zheng Ying Sheng James Liu, Ke Bao, and others LMSYS Org) for their merge and careful evaluation of EAGLE-3 on SGLang. 🤝Want to collaborate? We're a small academic group with limited GPU resources. If you're interested in supporting our next version of EAGLE or would like us to train a preliminary version tailored to a specific model, please get in touch! Joint work with Yuhui Li, Fangyun Wei, and Chao Zhang

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Can $300 RTX3060 be faster than $10,000 A100 for LLM decoding?🧐Yes Introduce EAGLE-2: - 4.26x🚀vanilla (13B) - 1.4x🚀EAGLE (13B) - No extra training than EAGLE - Maintain distribution Paper: Code: Demo:
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Can $300 RTX3060 be faster than $10,000 A100 for LLM decoding?🧐Yes Introduce EAGLE-2: - 4.26x🚀vanilla (13B) - 1.4x🚀EAGLE (13B) - No extra training than EAGLE - Maintain distribution Paper: Code: Demo:

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EAGLE-3 introduces two key innovations: Training-Time Testing (TTT) and multi-level feature fusion. By removing the feature prediction constraint used in previous EAGLE versions and leveraging semantic features across multiple layers, EAGLE-3 achieves higher acceptance rates, faster generation, and lossless performance. The result? - 5.6× faster than vanilla decoding (13B) Compared to EAGLE-1, EAGLE-3 delivers a 1.8× speedup on the 13B model, with the future EAGLE-4 release expected to further improve decoding efficiency. *Inference on the video conducted on 2x RTX 3090 GPUs at fp16 precision using the Vicuna 13B model.
0:12

EAGLE-3 introduces two key innovations: Training-Time Testing (TTT) and multi-level feature fusion. By removing the feature prediction constraint used in previous EAGLE versions and leveraging semantic features across multiple layers, EAGLE-3 achieves higher acceptance rates, faster generation, and lossless performance. The result? - 5.6× faster than vanilla decoding (13B) Compared to EAGLE-1, EAGLE-3 delivers a 1.8× speedup on the 13B model, with the future EAGLE-4 release expected to further improve decoding efficiency. *Inference on the video conducted on 2x RTX 3090 GPUs at fp16 precision using the Vicuna 13B model.

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🧵🚀 New WebAgent Benchmark Alert! 🚀 There is hope for human workers! We released WorkArena++, a new challenging benchmark for WebAgents. Our best agent achieves 0% accuracy on this benchmark, while human evaluators still obtain 94%! 🔗

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🚀 "AI Dreams of the Eyes of Its Creator" by Marc Quinn is now live and available to mint on: This groundbreaking collection from an iconic contemporary artist showcases the first 2 editions in a series of 8, crafted by a cutting-edge AI trained on Quinn’s iconic iris portraits.

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Running more than one team on Telegram? Create up to 10 separate organizations. Each one its own structure, its own view, its own members. Takes less than a minute and is visible to your whole team the second you set it up. Get the full app for free with beta access. Waitlist in first reply.

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🚀 Big news! The Soneium 💿 Mainnet is officially live! 🎉 This next-gen blockchain ecosystem, developed by Sony and Startale, merges the power of Ethereum Layer 2 with a focus on scalability, security, and user-friendliness. 🌐 Join us on this exciting journey! 🧵1/10

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Want 100× on every ORE you farm? Day 5 of the Advent Calendar is the first of it's kind 🎄 Trade in the BTC/ZIG pool on Oroswap and get a 100× ORE multiplier for 20 days. The top 3 wallets by trading volume will win a 100× ORE multiplier, the biggest multiplier on any trading platform, applied to all OREs earned in the next 20 days 🚀🚀 Trade here 👉

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Prediction Market is one of the leading Web3 niches in 2024! With about $4 Billion in trading volume, $192 Million in TVL and millions of users in 2024, prediction protocols have been showing tremendous growth and attracting user adoption in Web3. PolyMarket seems to be leading the pack, with over $175M in TVL, and backing from Vitalik Buterin. However, a majority of Prediction Markets, including PolyMarket, currently lacks the flexibility and capital efficiency required for seamless transactions. Also, they are all majorly focused on driving Web2 users thus neglecting the need for markets that cater for short-term, high-risk investments from Web3 Degens. To tackle these flaws, there's a need for a revolutionary contender that understands the need of Web3 Chads That's where Predict Hub comes in PredictHub is a prediction Market that transforms real world events into opportunities for everyone to participate and forecast. Launching on Arbitrum, PredictHub is already catching the attention of major players in the Space by offering something PolyMarket and others don't - Flexibility and Incentives. By offering fast market updates and innovative prediction category like ETF Forecasts, PredictHub is changing how we interact with Prediction Markets. But then, here's where it gets more interesting; PredictHub offer users a unique point system, where you don't just make predictions, you also earn rewards. The more you Predict, the more you earn. These rewards are 2-fold: Nova and Orbit Points. Nova Points are earned by traders based on their trading activity and their leaderboard ranking. Orbit Points, on the other hand, are earned by users who provide liquidity, based on their LP size and duration. Other Point systems include PolyMarket User Points, Leaderboard Bonus and Market Multipliers. These rewards offer users more competitive edge than other prediction markets. Apart from these rewards, PredictHub features a unique 3-tier referral system, rewarding users with even more as you invite your friends. The more friends you bring, the greater the rewards. On top of these, PredictHub focuses on USDC and a wide-range of yield bearing assets like GLP, gUSDC, and sUSDe, enabling users to optimise their earning while holding assets across Networks. Exciting, right? PredictHub is in its Testnet phase and you can start earning Points Right away 🔅 Here's how to Get Started on PredictHub: 1. Go to 2. Request Faucet 3. Start making predictions and earning Points Easy-Peasy ✅ More Info can be gotten from Predict Hub All eyes are on PredictHub as the fix for the flaws of Prediction Market Protocols. With its unique approach targeting untapped niches that most existing prediction markets have yet to explore, I believe the Protocol has the potential to become a breakout success I will be placing good Predictions to Position 🚀🚀🚀

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The EU–Viet Nam Comprehensive Strategic Partnership is more than a title on paper - it delivers concrete benefits for the people of Hanoi. Today, I visited the construction site of a metro station, supported by European funding, with contributions from the European Investment Bank , the European Commission, and France, Germany, and Italy. This is Team Europe in action.

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Why on earth does the US keep a for-profit healthcare system that delivers worse outcomes at higher costs than countries with universal healthcare? The answer is infuriating: For-profit healthcare has generated 51 billionaires on Forbes' annual billionaires list, and in a country ruled by profit, creating billionaires is more important than investing in the health and well-being of its own people.

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WTF is this? A startup announcing their benchmark in the sky! NEO ( Neo AI ) is shaking up the game and has stayed at #1 with 34.2% for 4 weeks. A multi-agent system with its own reasoning engine that not just plans and codes but executes the entire workflow, reducing the grunt work by 90% and saving ML teams thousands of hours.

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