Data Science | Machine Learning with Python for Researchers
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The Data Science and Python channel is for researchers and advanced programmers

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๐Ÿฆพ StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models

๐Ÿ–ฅ Github: https://github.com/yl4579/StyleTTS2

๐Ÿ”ฅColab: https://colab.research.google.com/github/yl4579/StyleTTS2/blob/main/

โšก๏ธ Demo: https://huggingface.co/spaces/styletts2/styletts2

๐Ÿ“š Paper: https://arxiv.org/abs/2306.07691

๐ŸŒŸ Demo: https://seamless.metademolab.com/expressive

๐Ÿฅฉ Page: styletts2.github.io
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Towards Learning a Generalist Model for Embodied Navigation

๐Ÿ–ฅ Github: https://github.com/zd11024/NaviLLM

๐Ÿ“• Paper: https://arxiv.org/pdf/2312.02010v1.pdf

๐Ÿ”ฅDatasets: https://paperswithcode.com/dataset/room-to-room

โœจ Tasks: https://paperswithcode.com/task/3d-question-answering-3d-qa
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๐Ÿ–ฅ Hitchhiker's Guide to Python

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๐Ÿ“š LlaVa Demo with LlamaIndex

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

๐Ÿ–ฅ Github: https://github.com/run-llama/llama_index/blob/main/docs/examples/multi_modal/llava_demo.ipynb

๐Ÿ” Colab: https://colab.research.google.com/github/run-llama/llama_index/blob/main/docs/examples/multi_modal/llava_demo.ipynb

๐Ÿชฉ Paper: https://arxiv.org/abs/2304.08485

๐Ÿ’ป Website: https://llava-vl.github.io/

๐Ÿ”ฅ YouTube: https://youtube.com/watch?v=k7i2BpeLUss
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โšก๏ธ UDiffText: A Unified Framework for High-quality Text Synthesis in Arbitrary Images via Character-aware Diffusion Models โœ’ Colab ๐Ÿฅณ

๐Ÿ–ฅ code: https://github.com/ZYM-PKU/UDiffText

โšก๏ธpage: https://udifftext.github.io

๐Ÿ“š paper: https://arxiv.org/abs/2312.04884

๐Ÿ”ฅcolab: https://github.com/camenduru/UDiffText-colab