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11. How to Generate Instruction Datasets from Any Documents for LLM Fine-Tuning

    Generate instruction datasets for fine-tuning Large Language Models (LLMs) using lightweight libraries and documents.

    2024-04-04 Tags: llm, fine-tuning, instruction datasets, towardsdatascience by klotz
12. Finetune LLMs on your own consumer hardware using tools from PyTorch and Hugging Face ecosystem | PyTorch

    efficient method for fine-tuning LLM using LoRA and QLoRA, making it possible to train them even on consumer hardware

    2024-01-12 Tags: llm, fine tuning, qlora, lora, peft, pytorch, hugging face, fine-tuning, llms by klotz
13. [2401.00908] DocLLM: A layout-aware generative language model for multimodal document understanding

    DocLLM is a lightweight extension to traditional LLMs for reasoning over visual documents, considering both textual semantics and spatial layout. It avoids expensive image encoders and focuses on bounding box information. It outperforms SotA LLMs on 14 out of 16 datasets across all tasks and generalizes well to previously unseen datasets.
    
    Keywords:

    2024-01-06 Tags: docllm, large language models, visual documents, textual semantics, spatial layout, pre-training, fine-tuning by klotz

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