• Host LLMs in Production With On-Demand GPUs Icon
    Host LLMs in Production With On-Demand GPUs

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    TorchDistill

    TorchDistill

    A coding-free framework built on PyTorch

    ...Even when you need to extract intermediate representations in teacher/student models, you will NOT need to reimplement the models, which often change the interface of the forward, but instead specify the module path(s) in the yaml file. In addition to knowledge distillation, 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
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  • 2
    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: 0 This Week
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  • 3
    AWS Toolkit for Visual Studio Code

    AWS Toolkit for Visual Studio Code

    Local Lambda debug, CodeWhisperer, SAM/CFN syntax, etc.

    The AWS Toolkit extension for Visual Studio Code enables you to interact with Amazon Web Services (AWS). Try the AWS Code Sample Catalog to start coding with the AWS SDK. The AWS Explorer provides access to the AWS services that you can work with when using the Toolkit. To see the AWS Explorer, choose the AWS icon in the Activity bar. The Developer Tools panel is a section for developer-focused tooling curated for working in an IDE. The Developer Tools panel can be found underneath the AWS Explorer when the AWS icon is selected in the Activity bar. ...
    Downloads: 2 This Week
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  • 4
    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 via composition blocks, allowing advanced research in parameter-efficient transfer learning for NLP tasks.
    Downloads: 0 This Week
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    $300 in Free Credit Across 150+ Cloud Services

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  • 5
    Next Generation Programming

    Next Generation Programming

    Compose Software Without Writing Any Programing Code

    "Next Generation Programming - Programming Without Coding Software" is a drag-drop wizard for creating simple or complex applications without writing any programming language code The Software is coded/designed with "Java Programming Language" for novice/expert programmers; Programmers can write softwares with visual tools : drag-drop components;visual editors... Programmers can use the software to compose of simple/complex applications : Database programs, circuit design, generate code and upload to chip for designed circuits (ESP8266, ESP32 chips) The Software in question is much simpler to use than PWCT (https://sourceforge.net/projects/doublesvsoop/) software. ...
    Downloads: 11 This Week
    Last Update:
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