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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
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📥 Don’t be Contradicted with Anything!CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System

Github: https://github.com/yizhen20133868/ci-tod

Paper: https://arxiv.org/abs/2109.11292v1

Dataset: https://paperswithcode.com/dataset/kvret-1

@ai_machinelearning_big_data
🧍‍♂ PASS: Pictures without humAns for Self-Supervised Pretraining

PASS is a large-scale image dataset that does not include any humans, human parts, or other personally identifiable information.

Github: https://github.com/yukimasano/PASS

Paper: https://arxiv.org/abs/2109.13228v1

Dataset: https://paperswithcode.com/dataset/pass

Documentation: https://www.robots.ox.ac.uk/~vgg/research/pass/

@ai_machinelearning_big_data
🧠 С момента выкладки библиотеки CatBoost в опенсорс прошло 100 лет! (Это если считать в двоичной системе счисления). Но главная новость в другом: библиотека обновилась до версии 1.0.0 и достигла состояния «production ready».

Более подробно обо всём этом читайте на Хабре: https://habr.com/ru/company/yandex/blog/580950/

@ai_machinelearning_big_data
🤖 MiniHack is a sandbox framework for easily designing rich and diverse environments for Reinforcement Learning

Github: https://github.com/facebookresearch/minihack

Facebook AI: https://ai.facebook.com/blog/minihack-a-new-sandbox-for-open-ended-reinforcement-learning/

Paper: https://arxiv.org/abs/2109.13202

Documentation: https://minihack.readthedocs.io/

@ai_machinelearning_big_data
🚀 Fast bottom-up method that jointly detects over 100 keypoints on humans or objects

Github: https://github.com/duncanzauss/keypoint_communities

Paper: https://arxiv.org/abs/2110.00988v1

Dataset: https://paperswithcode.com/dataset/coco

@ai_machinelearning_big_data
🧷 SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model.

Github: https://github.com/slundberg/shap

Paper: https://arxiv.org/abs/2110.03309v1

@ai_machinelearning_big_data
LightSeq: A High Performance Library for Sequence Processing and Generation

Github: https://github.com/bytedance/lightseq

Paper: https://arxiv.org/abs/2110.05722v1

A Guide of LightSeq Training: https://github.com/bytedance/lightseq/blob/master/docs/guide.md

@ai_machinelearning_big_data
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🍾 Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)

Github: https://github.com/jbeomlee93/rib

Paper: http://arxiv.org/abs/2110.06530

Dataset: https://paperswithcode.com/dataset/coco

@ai_machinelearning_big_data
📄 HRFormer: High-Resolution Transformer for Dense Prediction, NeurIPS 2021

Github: https://github.com/HRNet/HRFormer

Paper: https://arxiv.org/abs/2110.09408v1

Dataset: https://paperswithcode.com/dataset/coco

@ai_machinelearning_big_data