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Dot is designed to easily interact with documents and files (.pdf, .docx, .xlsx, .pptx, .md) using local LLMs and Retrieval Augmented Generation technology.
Dot was inspired by solutions like Nvidia's Chat with RTX
Defaults to Phi-3
https://t.me/DataScienceT
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Looking for a Remote Job? 💻🌍
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🐍 Python ➡️ https://t.me/remote_python_jobs
🔮 AI/ML/DS ➡️ https://t.me/remote_ai_jobs
☕️Java ➡️ https://t.me/remote_java_jobs
🐘 PHP ➡️ https://t.me/remote_php_jobs
♦️ Ruby ➡️ https://t.me/remote_ruby_job
🧑💻GO Lang ➡️ https://t.me/remote_go_jobs
🚀 DevOPS ➡️ https://t.me/remote_devops_jobs
💼 FrondEnd ➡️ https://t.me/remote_frontend_jobs
📱Mobile ➡️ https://t.me/remote_mobile_jobs
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🎁 Lisa has given away over $100,000 in the last 30 days. Every single one of her subscribers is making money.
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1. Subscribe to her channel
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InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature Interpretation
🖥 Github: https://github.com/jacobyhsi/InterpreTabNet
📕 Paper: https://arxiv.org/abs/2406.00426v1
https://t.me/DataScienceT✅
https://t.me/DataScienceT
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Alibaba has just released their new family of multilingual models that outperform the Llama 3 in many ways.
https://t.me/DataScienceT
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Forwarded from 🐳
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1mil+ people trust us, 226k native users on @whalesocials, and the community is only growing!
Share your thoughts and feedback of @Whale on Ton.app and Trustpilot. You make us better
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Flash Diffusion - acceleration of any diffusion model for image generation in a few steps
This is the name of the work recently published by Clément Chadebec, Onur Tasar and their colleagues.
This is a distillation method for creating fast diffusion patterns.
When training the model using this method on the COCO2014 and COCO2017 datasets, the FID and CLIP-Score achieve good values; it requires only a few hours of training on the GPU and fewer model parameters than existing methods require.
🟡 Flash Diffusion page
🖥 GitHub
🤗 Flash SD
🤗 Flash SDXL
https://t.me/DataScienceT✅
This is the name of the work recently published by Clément Chadebec, Onur Tasar and their colleagues.
This is a distillation method for creating fast diffusion patterns.
When training the model using this method on the COCO2014 and COCO2017 datasets, the FID and CLIP-Score achieve good values; it requires only a few hours of training on the GPU and fewer model parameters than existing methods require.
https://t.me/DataScienceT
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https://t.me/DataScienceT
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🎁 Lisa has given away over $100,000 in the last 30 days. Every single one of her subscribers is making money.
She is a professional trader and broadcasts her way of making money trading on her channel EVERY subscriber she has helped, and she will help you.
🧠 Do this and she will help you earn :
1. Subscribe to her channel
2. Write “GIFT” to her private messages
3. Follow her channel and trade with her. Repeat transactions after her = earn a lot of money.
Subscribe 👇🏻
https://t.me/+VwDs29eEzRA5MTAx
She is a professional trader and broadcasts her way of making money trading on her channel EVERY subscriber she has helped, and she will help you.
🧠 Do this and she will help you earn :
1. Subscribe to her channel
2. Write “GIFT” to her private messages
3. Follow her channel and trade with her. Repeat transactions after her = earn a lot of money.
Subscribe 👇🏻
https://t.me/+VwDs29eEzRA5MTAx
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The new Intel- L-MAGIC model can generate high-quality panoramic scenes based on a single input image and text prompt!
Numerous tests show that the model generates panoramic scenes with better scene placement and rendering quality than similar models.
▪️Github: https://github.com/IntelLabs/MMPano
▪️Paper: https://arxiv.org/abs/2406.01843
▪️Project: https://zhipengcai.github.io/MMPano/
▪️Video: https://youtu.be/XDMNEzH4-Ec
https://t.me/DataScienceT
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In this article, Microsoft introduced VALL-E 2, the latest advancement in language models , which marks a major milestone in text-to-speech (TTS) synthesis, reaching the human level for the first time.
Experiments with LibriSpeech and VCTK datasets have shown that VALL-E 2 outperforms all previous models in terms of generated speech quality and naturalness.
https://t.me/DataScienceT
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