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TON is Hosting Three-Day Offline Marathons for Developers in 13 Cities Worldwide
TON (The Open Network), a blockchain integrated into Telegram, is currently holding the largest hackathon in its history, “The Open League Hackathon,” with a prize pool of $2,000,000!
To support the hackathon, TON Society is organizing offline events around the world, giving Web3 enthusiasts the opportunity to spend three days immersed in development and networking.
📍 The marathons will take place in Prague, Berlin, Kyiv, Warsaw, Tbilisi, Belgrade, Seoul, Taipei (Taiwan), Gurugram (India), Hong Kong, Minsk, Moscow, and Saint Petersburg. The first events start on May 24th, so hurry up and register!
🔥 Why you should participate:
— 3 days of networking, lectures, competitions, and working on your own projects with continuous support from TON Foundation representatives and teams from the TON ecosystem. You can also join online.
— $5,000 prize for the top three projects at each offline event + plenty of merchandise and other bonuses.
Don’t miss the chance to present your mini-application to 900 million active Telegram users with TON.
Check the marathon schedule and details here - sign up and don't miss out on this great opportunity!
For guaranteed application review and other inquiries, contact the community manager @kate_shuffle
TON (The Open Network), a blockchain integrated into Telegram, is currently holding the largest hackathon in its history, “The Open League Hackathon,” with a prize pool of $2,000,000!
To support the hackathon, TON Society is organizing offline events around the world, giving Web3 enthusiasts the opportunity to spend three days immersed in development and networking.
📍 The marathons will take place in Prague, Berlin, Kyiv, Warsaw, Tbilisi, Belgrade, Seoul, Taipei (Taiwan), Gurugram (India), Hong Kong, Minsk, Moscow, and Saint Petersburg. The first events start on May 24th, so hurry up and register!
🔥 Why you should participate:
— 3 days of networking, lectures, competitions, and working on your own projects with continuous support from TON Foundation representatives and teams from the TON ecosystem. You can also join online.
— $5,000 prize for the top three projects at each offline event + plenty of merchandise and other bonuses.
Don’t miss the chance to present your mini-application to 900 million active Telegram users with TON.
Check the marathon schedule and details here - sign up and don't miss out on this great opportunity!
For guaranteed application review and other inquiries, contact the community manager @kate_shuffle
TON
Your Digital Passport in TON Ecosystem
Build your reputation with every app you use and every contribution you make.
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Works with video and photos.
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⚡️ Adobe has released DMD2!
A new and improved distillation method that can turn diffusion models such as SDXL into powerful one-step image generators.
It's been a while since we've seen any interesting updates to the SD ecosystem, so this is cool 🔥
▪ Project page: https://tianweiy.github.io/dmd2/
▪ Code: https://github.com/tianweiy/DMD2
▪ Demo: https://4e4a5c6a8b08f76802.gradio.live
🌐 http://t.me/codeprogrammer ✅️
A new and improved distillation method that can turn diffusion models such as SDXL into powerful one-step image generators.
It's been a while since we've seen any interesting updates to the SD ecosystem, so this is cool 🔥
▪ Project page: https://tianweiy.github.io/dmd2/
▪ Code: https://github.com/tianweiy/DMD2
▪ Demo: https://4e4a5c6a8b08f76802.gradio.live
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📘 Doctoral thesis
🏢 University: University of Notre Dame, Indiana
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Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI
🖥 Github: https://github.com/935963004/labram
📕Paper: https://arxiv.org/abs/2405.18765v1
#machineLearning
✅ https://news.1rj.ru/str/DataScienceT
🖥 Github: https://github.com/935963004/labram
📕Paper: https://arxiv.org/abs/2405.18765v1
#machineLearning
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https://news.1rj.ru/str/Hamster_kombat_bot/start?startapp=kentId418788114
💵 2 thousand coins as a gift for the first time
☄️ 25 thousand coins if you have Telegram Premium
Hamster will be listed on Ton Network soon
The experience is quite similar to that of the NOTCOIN bot💠
Hamster will be listed on Ton Network soon
The experience is quite similar to that of the NOTCOIN bot
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Telegram
Hamster Verse
Denoscription: Welcome to the HamsterVerse!
Play, have fun, and earn $HMSTR in the amazing games across our ecosystem.
Big updates are coming soon!
Play, have fun, and earn $HMSTR in the amazing games across our ecosystem.
Big updates are coming soon!
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InstaDrag is an approach that allows you to edit an image using a simple drag gesture in ~1 second.
At the same time, InstaDrag also copes with complex deformations of part of the image that are not represented in the training data (such deformations are, for example, elongation of hair, curvature of the rainbow, etc.).
There are plans to integrate InstaDrag with SDXL in the future
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Utilizes SDXL Flash and Scribble SDXL, making it even faster to get quality images from simple sketches and doodles
🤗 Launch on Hugging Face
https://news.1rj.ru/str/DataScienceT
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Forwarded from 🐳
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There are many games on our licensed platform where you can make a big jackpot!
Forget about registration – play and cash out your prizes right from Telegram.
Join now and win big with @whale
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The V-Express method was recently introduced by Cong Wang, Kuan Tian, Jun Zhang and others as one of the most efficient methods for generating such animations, the code and model are published
https://news.1rj.ru/str/DataScienceT
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conda create --name unsloth_env python=3.10
conda activate unsloth_env
conda install pytorch-cuda=<12.1/11.8> pytorch cudatoolkit xformers -c pytorch -c nvidia -c xformers
pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
pip install --no-deps trl peft accelerate bitsandbytes
Some unsloth benchmarks are given here
https://news.1rj.ru/str/DataScienceT
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-
pip install gpt-researcherExample of using GPT Researcher:
from gpt_researcher import GPTResearcher
query = "why is Nvidia stock going up?"
researcher = GPTResearcher(query=query, report_type="research_report")
# Conduct research on the given query
research_result = await researcher.conduct_research()
# Write the report
report = await researcher.write_report()
https://news.1rj.ru/str/DataScienceT
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Forwarded from ُEng. Hussein Sheikho
In this session, we will guide you through:
https://www.buildfastwithai.com/events/gpt-4o-deep-dive
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