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- 📢 Gate Square #Creator Campaign Phase 2# is officially live!
Join the ZKWASM event series, share your insights, and win a share of 4,000 $ZKWASM!
As a pioneer in zk-based public chains, ZKWASM is now being prominently promoted on the Gate platform!
Three major campaigns are launching simultaneously: Launchpool subscription, CandyDrop airdrop, and Alpha exclusive trading — don’t miss out!
🎨 Campaign 1: Post on Gate Square and win content rewards
📅 Time: July 25, 22:00 – July 29, 22:00 (UTC+8)
📌 How to participate:
Post original content (at least 100 words) on Gate Square related to
- 📢 Gate Square #MBG Posting Challenge# is Live— Post for MBG Rewards!
Want a share of 1,000 MBG? Get involved now—show your insights and real participation to become an MBG promoter!
💰 20 top posts will each win 50 MBG!
How to Participate:
1️⃣ Research the MBG project
Share your in-depth views on MBG’s fundamentals, community governance, development goals, and tokenomics, etc.
2️⃣ Join and share your real experience
Take part in MBG activities (CandyDrop, Launchpool, or spot trading), and post your screenshots, earnings, or step-by-step tutorials. Content can include profits, beginner-friendl
Babbitt News, recently, Shanghai Artificial Intelligence Laboratory (Shanghai AI Laboratory) released XTuner, an open source toolbox for large model training, which once again lowered the threshold for large model training. It is reported that XTuner focuses on the fine-tuning process, providing a lightweight fine-tuning framework for various open source large models, once again consolidating the practical tool attributes of the full-chain open source system. XTuner supports the adaptation of multiple levels of hardware. Developers only need to use a minimum of 8 GB of consumer-grade video memory to train an "exclusive large model" suitable for specific demand scenarios.