No learning rates needed: Introducing SALSA - Stable Armijo Line Search Adaptation
🖥 Github: https://github.com/themody/no-learning-rates-needed-introducing-salsa-stable-armijo-line-search-adaptation
📕 Paper: https://arxiv.org/abs/2407.20650v1
🚀 Dataset: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
🚀 Dataset: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
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DeepInteraction & DeepInteraction++
🖥 Github: https://github.com/fudan-zvg/deepinteraction
📕 Paper: https://arxiv.org/abs/2408.05075v1
🚀 Dataset: https://paperswithcode.com/dataset/nuscenes
@ArtificialIntelligencedl
🚀 Dataset: https://paperswithcode.com/dataset/nuscenes
@ArtificialIntelligencedl
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✔ SLCA++: Unleash the Power of Sequential Fine-tuning for Continual Learning with Pre-training
🖥 Github: github.com/gengdavid/slca
📕 Paper: https://arxiv.org/abs/2408.08295v1
🚀 Dataset: https://paperswithcode.com/dataset/imagenet-r
@ArtificialIntelligencedl
🚀 Dataset: https://paperswithcode.com/dataset/imagenet-r
@ArtificialIntelligencedl
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Forwarded from Machinelearning
Экосистема Fluх развивается очень быстро, каждый день появляются новые способы, решения, возможности и инструменты для работы с моделями Fluх онлайн и оффлайн.
Теперь у сообщества FLUX появился обновляемый и упорядоченный Awesome FLUX!
https://awesomeflux.com/
@ai_machinelearning_big_data
#AI #FLUX #ML #Awesome
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Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks
🖥 Github: https://github.com/tencent-ailab/hokoff
📕 Paper: https://arxiv.org/abs/2408.10556v1
🚀 Dataset: https://paperswithcode.com/dataset/d4rl
@ArtificialIntelligencedl
🚀 Dataset: https://paperswithcode.com/dataset/d4rl
@ArtificialIntelligencedl
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SAM & SAM 2 for Medical Image Segmentation.
🖥 Github: https://github.com/yichizhang98/sam4mis
📕 Paper: https://arxiv.org/abs/2408.12889v1
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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All Points Matter: Entropy-Regularized Distribution Alignment for Weakly-supervised 3D Segmentation (NeurIPS 2023)
🖥 Github: https://github.com/LiyaoTang/ERDA
📕 Paper: https://arxiv.org/abs/2408.16520v1
🚀 Dataset: https://paperswithcode.com/dataset/cityscapes
@ArtificialIntelligencedl
🚀 Dataset: https://paperswithcode.com/dataset/cityscapes
@ArtificialIntelligencedl
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⚡️ ART - Actually Robust Training
🖥 Github: https://github.com/sebchw/actually-robust-training
📕 Paper: https://arxiv.org/abs/2408.16285v1
@ArtificialIntelligencedl
pip install art-training
@ArtificialIntelligencedl
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aTENNuate: is a network that can be configured for real-time speech enhancement on raw audio waveforms.
🖥 Github: https://github.com/Brainchip-Inc/aTENNuate
📕 Paper: https://arxiv.org/abs/2409.03377v1
🚀 Dataset: https://paperswithcode.com/dataset/deep-noise-suppression-2020
@ArtificialIntelligencedl
🚀 Dataset: https://paperswithcode.com/dataset/deep-noise-suppression-2020
@ArtificialIntelligencedl
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⚡️Легкий способ получать свежие обновления и следить за трендами в разработке на вашем языке. Находите свой стек и подписывайтесь:
МАШИННОЕ ОБУЧЕНИЕ: www.group-telegram.com/ai_machinelearning_big_data
C++ www.group-telegram.com/cpluspluc
Python: www.group-telegram.com/pro_python_code
Хакинг: www.group-telegram.com/linuxkalii
Devops: www.group-telegram.com/devOPSitsec
АНАЛИЗ Данных: www.group-telegram.com/data_analysis_ml
Javascript: www.group-telegram.com/javascriptv
C#: www.group-telegram.com/csharp_ci
Java: www.group-telegram.com/javatg
Базы данных: www.group-telegram.com/sqlhub
Linux: www.group-telegram.com/linuxacademiya
Python собеседования: www.group-telegram.com/python_job_interview
Мобильная разработка: www.group-telegram.com/mobdevelop
Docker: www.group-telegram.com/DevopsDocker
Golang: www.group-telegram.com/golang_interview
React: www.group-telegram.com/react_tg
Rust: www.group-telegram.com/rust_code
PHP: www.group-telegram.com/phpshka
Android: www.group-telegram.com/android_its
Frontend: www.group-telegram.com/front
Big Data: www.group-telegram.com/bigdatai
Собеседования МЛ: www.group-telegram.com/machinelearning_interview
МАТЕМАТИКА: www.group-telegram.com/data_math
Kubernets: www.group-telegram.com/kubernetc
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Папка ML: https://www.group-telegram.com/addlist/2Ls-snqEeytkMDgy
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😆ИТ-Мемы: www.group-telegram.com/memes_prog
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🎓954ГБ ОПЕНСОРС КУРСОВ: @courses
📕Ит-книги бесплатно: https://www.group-telegram.com/addlist/BkskQciUW_FhNjEy
МАШИННОЕ ОБУЧЕНИЕ: www.group-telegram.com/ai_machinelearning_big_data
C++ www.group-telegram.com/cpluspluc
Python: www.group-telegram.com/pro_python_code
Хакинг: www.group-telegram.com/linuxkalii
Devops: www.group-telegram.com/devOPSitsec
АНАЛИЗ Данных: www.group-telegram.com/data_analysis_ml
Javascript: www.group-telegram.com/javascriptv
C#: www.group-telegram.com/csharp_ci
Java: www.group-telegram.com/javatg
Базы данных: www.group-telegram.com/sqlhub
Linux: www.group-telegram.com/linuxacademiya
Python собеседования: www.group-telegram.com/python_job_interview
Мобильная разработка: www.group-telegram.com/mobdevelop
Docker: www.group-telegram.com/DevopsDocker
Golang: www.group-telegram.com/golang_interview
React: www.group-telegram.com/react_tg
Rust: www.group-telegram.com/rust_code
PHP: www.group-telegram.com/phpshka
Android: www.group-telegram.com/android_its
Frontend: www.group-telegram.com/front
Big Data: www.group-telegram.com/bigdatai
Собеседования МЛ: www.group-telegram.com/machinelearning_interview
МАТЕМАТИКА: www.group-telegram.com/data_math
Kubernets: www.group-telegram.com/kubernetc
💼 Папка с вакансиями: www.group-telegram.com/addlist/_zyy_jQ_QUsyM2Vi
Папка Go разработчика: www.group-telegram.com/addlist/MUtJEeJSxeY2YTFi
Папка Python разработчика: www.group-telegram.com/addlist/eEPya-HF6mkxMGIy
Папка ML: https://www.group-telegram.com/addlist/2Ls-snqEeytkMDgy
Папка FRONTEND: https://www.group-telegram.com/addlist/mzMMG3RPZhY2M2Iy
😆ИТ-Мемы: www.group-telegram.com/memes_prog
🇬🇧Английский: www.group-telegram.com/english_forprogrammers
🧠ИИ: www.group-telegram.com/vistehno
🎓954ГБ ОПЕНСОРС КУРСОВ: @courses
📕Ит-книги бесплатно: https://www.group-telegram.com/addlist/BkskQciUW_FhNjEy
Telegram
Machinelearning
Погружаемся в машинное обучение и Data Science
Показываем как запускать любые LLm на пальцах.
По всем вопросам - @haarrp
@itchannels_telegram -🔥best channels
Реестр РКН: clck.ru/3Fmqri
Показываем как запускать любые LLm на пальцах.
По всем вопросам - @haarrp
@itchannels_telegram -🔥best channels
Реестр РКН: clck.ru/3Fmqri
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UniMERNet: A Universal Network for Real-World Mathematical Expression Recognition
🖥 Github: https://github.com/opendatalab/unimernet
📕 Paper: https://arxiv.org/pdf/2409.03643v1
🚀 Dataset: https://opendatalab.com/OpenDataLab/UniMER-Dataset
🤗 HF: https://huggingface.co/datasets/wanderkid/UniMER_Dataset
@ArtificialIntelligencedl
🚀 Dataset: https://opendatalab.com/OpenDataLab/UniMER-Dataset
🤗 HF: https://huggingface.co/datasets/wanderkid/UniMER_Dataset
@ArtificialIntelligencedl
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LLaMA-Omni: Seamless Speech Interaction with Large Language Models
🖥 Github: https://github.com/ictnlp/llama-omni
📕 Paper: https://arxiv.org/abs/2409.06666
🤗 HF: https://huggingface.co/ICTNLP/Llama-3.1-8B-Omni
@ArtificialIntelligencedl
🤗 HF: https://huggingface.co/ICTNLP/Llama-3.1-8B-Omni
@ArtificialIntelligencedl
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💡 1M-Deepfakes Detection Challenge
🖥 Github: https://github.com/controlnet/av-deepfake1m
📕 Paper: https://arxiv.org/abs/2409.06991v1
⚡️ Dataset: https://paperswithcode.com/dataset/celeb-df
@ArtificialIntelligencedl
⚡️ Dataset: https://paperswithcode.com/dataset/celeb-df
@ArtificialIntelligencedl
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GitHub
GitHub - ControlNet/AV-Deepfake1M: [ACM MM Award] AV-Deepfake1M: A Large-Scale LLM-Driven Audio-Visual Deepfake Dataset
[ACM MM Award] AV-Deepfake1M: A Large-Scale LLM-Driven Audio-Visual Deepfake Dataset - ControlNet/AV-Deepfake1M
SGFormer: Simplified Graph Transformers
🖥 Github: https://github.com/qitianwu/sgformer
📕 Paper: https://arxiv.org/pdf/2306.10759.pdf
🤗 Blog: https://zhuanlan.zhihu.com/p/674548352
@ArtificialIntelligencedl
🤗 Blog: https://zhuanlan.zhihu.com/p/674548352
@ArtificialIntelligencedl
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OmniGen: Unified Image Generation
🖥 Github: https://github.com/vectorspacelab/omnigen
📕 Paper: https://arxiv.org/abs/2409.11340v1
🤗 Dataset: https://paperswithcode.com/dataset/dreambench
@ArtificialIntelligencedl
🤗 Dataset: https://paperswithcode.com/dataset/dreambench
@ArtificialIntelligencedl
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LLM based Multi-Agent methods
🖥 Github: https://github.com/AgnostiqHQ/multi-agent-llm
📕 Paper: https://arxiv.org/abs/2409.12618v1
🤗 Dataset: https://paperswithcode.com/dataset/hotpotqa
@ArtificialIntelligencedl
🤗 Dataset: https://paperswithcode.com/dataset/hotpotqa
@ArtificialIntelligencedl
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🚀 FlowTurbo: Towards Real-time Flow-Based Image Generation with Velocity Refiner (NeurIPS 2024)
🖥 Github: https://github.com/shiml20/flowturbo
📕 Paper: https://arxiv.org/abs/2409.18128v1
🤗 Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
git clone https://github.com/shiml20/FlowTurbo.git
cd FlowTurbo
🤗 Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
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How to Train Long-Context Language Models (Effectively)
🖥 Github: https://github.com/hijkzzz/pymarl2
📕 Paper: https://arxiv.org/abs/2410.02511v1
🤗 Dataset: https://paperswithcode.com/dataset/smac
@ArtificialIntelligencedl
🤗 Dataset: https://paperswithcode.com/dataset/smac
@ArtificialIntelligencedl
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