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  • 1
    AdalFlow

    AdalFlow

    The library to build & auto-optimize LLM applications

    AdalFlow is a framework for building AI-powered automation workflows, enabling users to design and execute intelligent automation pipelines with minimal coding.
    Downloads: 1 This Week
    Last Update:
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  • 2
    TorchDistill

    TorchDistill

    A coding-free framework built on PyTorch

    ..., this framework helps you design and perform general deep learning experiments (WITHOUT coding) for reproducible deep learning studies. i.e., it enables you to train models without teachers simply by excluding teacher entries from a declarative yaml config file.
    Downloads: 0 This Week
    Last Update:
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  • 3
    Adapters

    Adapters

    A Unified Library for Parameter-Efficient Learning

    Adapters is an add-on library to HuggingFace's Transformers, integrating 10+ adapter methods into 20+ state-of-the-art Transformer models with minimal coding overhead for training and inference. Adapters provide a unified interface for efficient fine-tuning and modular transfer learning, supporting a myriad of features like full-precision or quantized training (e.g. Q-LoRA, Q-Bottleneck Adapters, or Q-PrefixTuning), adapter merging via task arithmetics or the composition of multiple adapters...
    Downloads: 0 This Week
    Last Update:
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