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AnimateDiff
Effective framework to animate most of existing personalized text-to-image models once for all, saving the efforts in model-specific tuning.
🖥 Github: https://github.com/guoyww/animatediff/
🖥 Colab: https://colab.research.google.com/github/camenduru/AnimateDiff-colab/blob/main/AnimateDiff_colab.ipynb
📕 Paper: https://arxiv.org/abs/2307.04725
🚀 Project: https://animatediff.github.io/
https://news.1rj.ru/str/DataScienceT
Effective framework to animate most of existing personalized text-to-image models once for all, saving the efforts in model-specific tuning.
🖥 Github: https://github.com/guoyww/animatediff/
🖥 Colab: https://colab.research.google.com/github/camenduru/AnimateDiff-colab/blob/main/AnimateDiff_colab.ipynb
📕 Paper: https://arxiv.org/abs/2307.04725
🚀 Project: https://animatediff.github.io/
https://news.1rj.ru/str/DataScienceT
👍2
machinelearningAIDeep_resume.pdf
45.4 MB
Cheat Sheets for AI Neural Networks, Machine Learning, DeepLearning & Big Data
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🔈 Urhythmic: Rhythm Modeling for Voice Conversion
Unsupervised Rhythm Modeling for Voice Conversion.
🖥 Github: https://github.com/bshall/urhythmic
🖥 Documentation: https://colab.research.google.com/github/bshall/urhythmic/blob/main/urhythmic_demo.ipynb
📕 Paper: https://arxiv.org/abs/2307.06040v1
🚀 Dataset: https://paperswithcode.com/dataset/vctk
https://news.1rj.ru/str/DataScienceT
Unsupervised Rhythm Modeling for Voice Conversion.
🖥 Github: https://github.com/bshall/urhythmic
🖥 Documentation: https://colab.research.google.com/github/bshall/urhythmic/blob/main/urhythmic_demo.ipynb
📕 Paper: https://arxiv.org/abs/2307.06040v1
🚀 Dataset: https://paperswithcode.com/dataset/vctk
https://news.1rj.ru/str/DataScienceT
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Are you looking to break into Machine Learning?
Here is a great place to start:
This is the best video series about Neural Networks for anyone who wants to understand how they work.
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Here is a great place to start:
This is the best video series about Neural Networks for anyone who wants to understand how they work.
https://www.3blue1brown.com/topics/neural-networks
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Get up to speed on Large Language Models with these two free cheat sheets
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Extract Text From a Multi-Column Document Using PyMuPDF in Python
Code: https://artifex.com/blog/extract-text-from-a-multi-column-document-using-pymupdf-inpython
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Code: https://artifex.com/blog/extract-text-from-a-multi-column-document-using-pymupdf-inpython
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Image as Set of Points - ICLR'23 [Oral, Top5%]
🖥 Github: https://github.com/ma-xu/context-cluster
⏩ Paper: https://arxiv.org/abs/2303.01494v1
💨 Dataset: https://paperswithcode.com/dataset/scanobjectnn
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🖥 Github: https://github.com/ma-xu/context-cluster
⏩ Paper: https://arxiv.org/abs/2303.01494v1
💨 Dataset: https://paperswithcode.com/dataset/scanobjectnn
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🔥 Artificial Intelligence for Science (AIRS)
•OpenQM: AI for Quantum Mechanics
•OpenDFT: AI for Density Functional Theory
•OpenMol: AI for Small Molecules
•OpenProt: AI for Protein Science
•OpenMat: AI for Materials Science
•OpenMI: AI for Molecular Interactions
•OpenPDE: AI for Partial Differential Equations
🖥 Github: https://github.com/divelab/AIRS
📕 Paper: https://arxiv.org/abs/2307.08423
⭐️ Website: https://www.air4.science/
📌 Dataset: https://paperswithcode.com/dataset/atom3d
t.me/DataScienceT
•OpenQM: AI for Quantum Mechanics
•OpenDFT: AI for Density Functional Theory
•OpenMol: AI for Small Molecules
•OpenProt: AI for Protein Science
•OpenMat: AI for Materials Science
•OpenMI: AI for Molecular Interactions
•OpenPDE: AI for Partial Differential Equations
🖥 Github: https://github.com/divelab/AIRS
📕 Paper: https://arxiv.org/abs/2307.08423
⭐️ Website: https://www.air4.science/
📌 Dataset: https://paperswithcode.com/dataset/atom3d
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Neural Video Depth Stabilizer (ICCV2023) 🚀🚀🚀
🖥 Github: https://github.com/raymondwang987/nvds
⏩ Paper: https://arxiv.org/pdf/2307.08695v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/wsvd
https://news.1rj.ru/str/DataScienceT
🖥 Github: https://github.com/raymondwang987/nvds
⏩ Paper: https://arxiv.org/pdf/2307.08695v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/wsvd
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💬 Text2Cinemagraph: Synthesizing Artistic Cinemagraphs from Text
🖥 Github: https://github.com/text2cinemagraph/text2cinemagraph
🖥 Colab: https://colab.research.google.com/github/camenduru/AnimateDiff-colab/blob/main/AnimateDiff_colab.ipynb
📕 Paper: https://arxiv.org/pdf/2307.03190.pdf
🚀 Project: https://text2cinemagraph.github.io/website/
https://news.1rj.ru/str/DataScienceT
🖥 Github: https://github.com/text2cinemagraph/text2cinemagraph
🖥 Colab: https://colab.research.google.com/github/camenduru/AnimateDiff-colab/blob/main/AnimateDiff_colab.ipynb
📕 Paper: https://arxiv.org/pdf/2307.03190.pdf
🚀 Project: https://text2cinemagraph.github.io/website/
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🔥 Llama 2: Open Foundation and Fine-Tuned Chat Models
Llama 2 collection of pretrained and fine-tuned large language models (LLMs).
🖥 Github: https://github.com/facebookresearch/llama
⭐️ Demo: https://huggingface.co/blog/llama2
🤗Hugging face: https://huggingface.co/meta-llama/Llama-2-70b
📕 Paper: https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/
https://news.1rj.ru/str/DataScienceT
Llama 2 collection of pretrained and fine-tuned large language models (LLMs).
🖥 Github: https://github.com/facebookresearch/llama
⭐️ Demo: https://huggingface.co/blog/llama2
🤗Hugging face: https://huggingface.co/meta-llama/Llama-2-70b
📕 Paper: https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/
https://news.1rj.ru/str/DataScienceT
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SVDFormer: Complementing Point Cloud via Self-view Augmentation and Self-structure Dual-generator
🖥 Github: https://github.com/czvvd/svdformer
⏩ Paper: https://arxiv.org/pdf/2307.08492v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/shapenet
https://news.1rj.ru/str/DataScienceT
🖥 Github: https://github.com/czvvd/svdformer
⏩ Paper: https://arxiv.org/pdf/2307.08492v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/shapenet
https://news.1rj.ru/str/DataScienceT
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🌆Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback
🖥 Github: https://github.com/tetrzim/diffusion-human-feedback
⏩ Paper: https://arxiv.org/pdf/2307.02770v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/imagenet
https://news.1rj.ru/str/DataScienceT
🖥 Github: https://github.com/tetrzim/diffusion-human-feedback
⏩ Paper: https://arxiv.org/pdf/2307.02770v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/imagenet
https://news.1rj.ru/str/DataScienceT
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FLASK: Fine-grained Language Model Evaluation Based on Alignment Skill Sets
🖥 Github: https://github.com/kaistai/flask
⏩ Paper: https://arxiv.org/pdf/2307.10928v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/gsm8k
https://news.1rj.ru/str/DataScienceT
🖥 Github: https://github.com/kaistai/flask
⏩ Paper: https://arxiv.org/pdf/2307.10928v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/gsm8k
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Forwarded from Machine Learning with Python
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