Showing 3 open source projects for "port"

View related business solutions
  • Application Monitoring That Won't Slow Your App Down Icon
    Application Monitoring That Won't Slow Your App Down

    AppSignal's Rust-based agent is lightweight and stable. Already running in thousands of production apps.

    Full APM with errors, performance, logs, and uptime monitoring. 99.999% uptime SLA on the platform itself.
    Start Free
  • Forever Free Full-Stack Observability | Grafana Cloud Icon
    Forever Free Full-Stack Observability | Grafana Cloud

    Our generous forever free tier includes the full platform, including the AI Assistant, for 3 users with 10k metrics, 50GB logs, and 50GB traces.

    Built on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
    Create free account
  • 1
    Make-A-Video - Pytorch (wip)

    Make-A-Video - Pytorch (wip)

    Implementation of Make-A-Video, new SOTA text to video generator

    ...Passing in images (if one were to pretrain on images first), both temporal convolution and attention will be automatically skipped. In other words, you can use this straightforwardly in your 2d Unet and then port it over to a 3d Unet once that phase of the training is done.
    Downloads: 9 This Week
    Last Update:
    See Project
  • 2
    min(DALL·E)

    min(DALL·E)

    min(DALL·E) is a fast, minimal port of DALL·E Mini to PyTorch

    This is a fast, minimal port of Boris Dayma's DALL·E Mini (with mega weights). It has been stripped down for inference and converted to PyTorch. The only third-party dependencies are numpy, requests, pillow and torch. The required models will be downloaded to models_root if they are not already there. Set the dtype to torch.float16 to save GPU memory. If you have an Ampere architecture GPU you can use torch.bfloat16.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    FID score for PyTorch

    FID score for PyTorch

    Compute FID scores with PyTorch

    This is a port of the official implementation of Fréchet Inception Distance to PyTorch. FID is a measure of similarity between two datasets of images. It was shown to correlate well with human judgement of visual quality and is most often used to evaluate the quality of samples of Generative Adversarial Networks. FID is calculated by computing the Fréchet distance between two Gaussians fitted to feature representations of the Inception network.
    Downloads: 6 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB