Showing 3 open source projects for "virtual-auto-clicker"

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    Gemini 3 and 200+ AI Models on One Platform

    Access Google's best plus Claude, Llama, and Gemma. Fine-tune and deploy from one console.

    Build, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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    Add Two Lines of Code. Get Full APM.

    AppSignal installs in minutes and auto-configures dashboards, alerts, and error tracking.

    Works out of the box for Rails, Django, Express, Phoenix, and more. Monitoring exceptions and performance in no time.
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  • 1
    Diffusers

    Diffusers

    State-of-the-art diffusion models for image and audio generation

    ...Pretrained models that can be used as building blocks, and combined with schedulers, for creating your own end-to-end diffusion systems. We recommend installing Diffusers in a virtual environment from PyPi or Conda. For more details about installing PyTorch and Flax, please refer to their official documentation.
    Downloads: 7 This Week
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  • 2
    ImageReward

    ImageReward

    [NeurIPS 2023] ImageReward: Learning and Evaluating Human Preferences

    ImageReward is the first general-purpose human preference reward model (RM) designed for evaluating text-to-image generation, introduced alongside the NeurIPS 2023 paper ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation. Trained on 137k expert-annotated image pairs, ImageReward significantly outperforms existing scoring methods like CLIP, Aesthetic, and BLIP in capturing human visual preferences. It is provided as a Python package (image-reward) that enables...
    Downloads: 2 This Week
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  • 3
    DALL-E in Pytorch

    DALL-E in Pytorch

    Implementation / replication of DALL-E, OpenAI's Text to Image

    ...You can also skip the training of the VAE altogether, using the pretrained model released by OpenAI! The wrapper class should take care of downloading and caching the model for you auto-magically. You can also use the pretrained VAE offered by the authors of Taming Transformers! Currently only the VAE with a codebook size of 1024 is offered, with the hope that it may train a little faster than OpenAI's, which has a size of 8192. In contrast to OpenAI's VAE, it also has an extra layer of downsampling, so the image sequence length is 256 instead of 1024 (this will lead to a 16 reduction in training costs, when you do the math).
    Downloads: 0 This Week
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