ML Research Hub – Telegram
ML Research Hub
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Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

Admin: @HusseinSheikho || @Hussein_Sheikho
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🔥 Diffusion360: Seamless 360 Degree Panoramic Image Generation based on Diffusion Models.

🖥 Code: https://github.com/archerfmy/sd-t2i-360panoimage

📚 Paper: https://arxiv.org/abs/2311.13141v1

🔗 Dataset: https://paperswithcode.com/dataset/sun360

https://news.1rj.ru/str/DataScienceT
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🎮 Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch

🖥 Code: https://github.com/yule-BUAA/MergeLM

📚 Paper: https://arxiv.org/abs/2311.03099

🔗 Dataset: https://paperswithcode.com/task/instruction-following

https://news.1rj.ru/str/DataScienceT
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Forwarded from Data Science Library
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🦾 StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models

🖥 Github: https://github.com/yl4579/StyleTTS2

🔥Colab: https://colab.research.google.com/github/yl4579/StyleTTS2/blob/main/

⚡️ Demo: https://huggingface.co/spaces/styletts2/styletts2

📚 Paper: https://arxiv.org/abs/2306.07691

🌟 Demo: https://seamless.metademolab.com/expressive

🥩 Page: styletts2.github.io
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🖥 Hitchhiker's Guide to Python

Python Best Practices Guidebook

A guide to best practices for installing, configuring and using Python on a daily basis, including pip, numpy, virtualenv and more.

Resources: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A/110
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📚 LlaVa Demo with LlamaIndex

In this example, we illustrate how we use LlaVa for belowing tasks:
Retrieval Augmented Image Captioning
Pydantic Structured Output
Multi-Modal Retrieval-Augmented Generation (RAG) using Llava-13b

🖥 Github: https://github.com/run-llama/llama_index/blob/main/docs/examples/multi_modal/llava_demo.ipynb

🔍 Colab: https://colab.research.google.com/github/run-llama/llama_index/blob/main/docs/examples/multi_modal/llava_demo.ipynb

🪩 Paper: https://arxiv.org/abs/2304.08485

💻 Website: https://llava-vl.github.io/

🔥 YouTube: https://youtube.com/watch?v=k7i2BpeLUss
Forwarded from Data Analytics
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