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☄️Dataset Quantization

DQ is able to generate condensed small datasets for training unseen network architectures with state-of-the-art compression ratios for lossless model training.

Квантование наборов данных (DQ) - новая схема сжатия больших наборов данных в небольшие сабсеты, которые могут быть использованы для обучения любых нейросетевых архитектур.

git clone https://github.com/vimar-gu/DQ.git
cd DQ

🖥 Github: https://github.com/magic-research/dataset_quantization

📕 Paper: https://arxiv.org/abs/2308.10524v1

☑️ Dataset: https://paperswithcode.com/dataset/gsm8k

ai_machinelearning_big_data

Data Science by ODS.ai 🦜
Forwarded from Machinelearning
☄️Dataset Quantization

DQ is able to generate condensed small datasets for training unseen network architectures with state-of-the-art compression ratios for lossless model training.

Квантование наборов данных (DQ) - новая схема сжатия больших наборов данных в небольшие сабсеты, которые могут быть использованы для обучения любых нейросетевых архитектур.

git clone https://github.com/vimar-gu/DQ.git
cd DQ

🖥 Github: https://github.com/magic-research/dataset_quantization

📕 Paper: https://arxiv.org/abs/2308.10524v1

☑️ Dataset: https://paperswithcode.com/dataset/gsm8k

ai_machinelearning_big_data
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☄️Dataset Quantization

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