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Ebout Data Science | Дима Савелко@eboutdatascience P.76
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🏆 LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models

13B and 70B 32k models with the supervised fine-tuning, which is feasible for long context

LongLoRA - эффективный подход к файнтюнингу, позволяющий расширить размер контекста предварительно обученных больших языковых моделей (БЯМ) при ограниченных вычислительных затратах.

🖥 Github: https://github.com/dvlab-research/longlora

📕 Paper: https://arxiv.org/abs/2309.12307v1

⭐️ Demo: https://b3cfcf9e79ff42df5f.gradio.live/

Dataset: https://paperswithcode.com/dataset/pg-19

ai_machinelearning_big_data
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🏆 LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models

13B and 70B 32k models with the supervised fine-tuning, which is feasible for long context

LongLoRA - эффективный подход к файнтюнингу, позволяющий расширить размер контекста предварительно обученных больших языковых моделей (БЯМ) при ограниченных вычислительных затратах.

🖥 Github: https://github.com/dvlab-research/longlora

📕 Paper: https://arxiv.org/abs/2309.12307v1

⭐️ Demo: https://b3cfcf9e79ff42df5f.gradio.live/

Dataset: https://paperswithcode.com/dataset/pg-19

ai_machinelearning_big_data

BY Ebout Data Science | Дима Савелко





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