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    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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    Veeam Data Platform v13.1

    Move workloads across hypervisors and clouds with no vendor lock-in. Try VDP free today.

    Try Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
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  • 1
    bufferline.nvim

    bufferline.nvim

    A snazzy bufferline for Neovim

    A snazzy buffer line (with tab page integration) for Neovim built using Lua. This plugin shamelessly attempts to emulate the aesthetics of GUI text editors/Doom Emacs. It is advised that you specify either the latest tag or a specific tag and bump them manually if you'd prefer to inspect changes before updating.
    Downloads: 0 This Week
    Last Update:
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  • 2

    BallPlay Cupid

    Arcade puzzle game with balls

    BallPlay Cupid is an arcade puzzle games, in which you have a task to fulfil by changing the direction of the balls, by using tools. Complete the task and keep the required number of balls away from destruction.
    Downloads: 1 This Week
    Last Update:
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  • 3
    char-rnn

    char-rnn

    Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN)

    char-rnn is a classic codebase for training multi-layer recurrent neural networks on raw text to build character-level language models that learn to predict the next character in a sequence. It supports common recurrent architectures including vanilla RNNs as well as LSTM and GRU variants, letting users compare behavior and output quality across model types. It is straightforward: you provide a single text file, train the model to minimize next-character prediction loss, then sample from the trained network to generate new text one character at a time in the style of the dataset. The project is designed for experimentation, offering tunable settings for depth, hidden size, dropout, sequence length, and sampling temperature to control creativity and coherence. ...
    Downloads: 0 This Week
    Last Update:
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