Showing 2 open source projects for "python 3.7 decompiler"

View related business solutions
  • The Most Powerful Software Platform for EHSQ and ESG Management Icon
    The Most Powerful Software Platform for EHSQ and ESG Management

    Addresses the needs of small businesses and large global organizations with thousands of users in multiple locations.

    Choose from a complete set of software solutions across EHSQ that address all aspects of top performing Environmental, Health and Safety, and Quality management programs.
    Learn More
  • AestheticsPro Medical Spa Software Icon
    AestheticsPro Medical Spa Software

    Our new software release will dramatically improve your medspa business performance while enhancing the customer experience

    AestheticsPro is the most complete Aesthetics Software on the market today. HIPAA Cloud Compliant with electronic charting, integrated POS, targeted marketing and results driven reporting; AestheticsPro delivers the tools you need to manage your medical spa business. It is our mission To Provide an All-in-One Cutting Edge Software to the Aesthetics Industry.
    Learn More
  • 1
    Mangum

    Mangum

    AWS Lambda support for ASGI applications

    Mangum is an adapter for running ASGI applications in AWS Lambda to handle Function URL, API Gateway, ALB, and Lambda@Edge events. Event handlers for API Gateway HTTP and REST APIs, Application Load Balancer, Function URLs, and CloudFront Lambda@Edge. Compatibility with ASGI application frameworks, such as Starlette, FastAPI, Quart and Django. Support for binary media types and payload compression in API Gateway using GZip or Brotli. Works with existing deployment and configuration tools,...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    CLIP-as-service

    CLIP-as-service

    Embed images and sentences into fixed-length vectors

    CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a microservice into neural search solutions. Serve CLIP models with TensorRT, ONNX runtime and PyTorch w/o JIT with 800QPS[*]. Non-blocking duplex streaming on requests and responses, designed for large data and long-running tasks. Horizontally scale up and down multiple CLIP models on single GPU, with automatic load balancing. Easy-to-use. No learning curve, minimalist...
    Downloads: 1 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next