Showing 4 open source projects for "human resource"

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  • 1
    The Alignment Handbook

    The Alignment Handbook

    Robust recipes to align language models with human and AI preferences

    The Alignment Handbook is an open-source resource created to provide practical guidance for aligning large language models with human preferences and safety requirements. The project focuses on the post-training stage of model development, where models are refined after pre-training to behave more helpfully, safely, and reliably in real-world applications. It provides detailed training recipes that explain how to perform tasks such as supervised fine-tuning, preference modeling, and reinforcement learning from human feedback. ...
    Downloads: 0 This Week
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  • 2
    CAMEL AI

    CAMEL AI

    Finding the Scaling Law of Agents. A multi-agent framework

    ...Our approach involves using inception prompting to guide chat agents toward task completion while maintaining consistency with human intentions. We showcase how role-playing can be used to generate conversational data for studying the behaviors and capabilities of chat agents, providing a valuable resource for investigating conversational language models.
    Downloads: 1 This Week
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  • 3
    NLP

    NLP

    Open source NLP guide with models, methods, and real use cases

    NLP is an open source introductory resource for natural language processing, presented as a continuously updated book hosted on GitHub. It explains how machines process and understand human language, combining theory with practical examples. Its covers core NLP concepts such as text representation, feature extraction, and model evaluation, alongside hands-on implementations using tools like Word2Vec, TF-IDF, and FastText.
    Downloads: 0 This Week
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  • 4
    dots.ocr

    dots.ocr

    Multilingual Document Layout Parsing in a Single Vision-Language Model

    ...Unlike traditional OCR pipelines that rely on multiple specialized components, dots.ocr integrates these processes end-to-end, reducing error propagation and improving consistency across tasks. The model is designed to recognize virtually any human script, making it highly effective for global and low-resource language scenarios. It achieves state-of-the-art performance on document parsing benchmarks while maintaining a relatively compact model size, demonstrating efficiency without sacrificing accuracy. Beyond standard OCR tasks, it extends its capabilities to parse complex visual elements such as charts, diagrams, and web interfaces, converting them into structured outputs like SVG code.
    Downloads: 0 This Week
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