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  • 1
    Output

    Output

    TypeScript framework for building AI workflows and agents

    ...It eliminates reliance on fragmented SaaS tools by providing all necessary components locally, ensuring better transparency and control over data and processes. Output includes built-in evaluation systems, such as LLM-as-a-judge scoring, and integrates workflow orchestration tools like Temporal to handle retries, parallel execution, and state management. It also supports multiple model providers through a unified API.
    Downloads: 1 This Week
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  • 2
    StabilityMatrix

    StabilityMatrix

    Multi-Platform Package Manager for Stable Diffusion

    ...It provides a framework to run experiments systematically—capturing inputs, model configurations, outputs, and metrics—so researchers and practitioners can reason about differences in quality, robustness, and failure modes. The repository often bundles tooling for automated prompt sweeping, scoring heuristics (such as diversity, coherence, or task-specific metrics), and visualization helpers to make comparisons interpretable. This approach is useful for model selection, prompt engineering, and benchmarking new checkpoints against baseline models under reproducible conditions. By turning ad-hoc tests into tracked experiments, StabilityMatrix reduces bias, surfaces subtle regressions, and accelerates iteration when tuning generative systems.
    Downloads: 87 This Week
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  • 3
    BentoML

    BentoML

    Unified Model Serving Framework

    BentoML simplifies ML model deployment and serves your models at a production scale. Support multiple ML frameworks natively: Tensorflow, PyTorch, XGBoost, Scikit-Learn and many more! Define custom serving pipeline with pre-processing, post-processing and ensemble models. Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference...
    Downloads: 0 This Week
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  • 4
    GEPETTO - Gene Prioritization in Java

    GEPETTO - Gene Prioritization in Java

    GEPETTO (GEne Prioritization ExTended TOol)

    ...GEPETTO is written in Java/Python and supported by an advanced modular architecture, which means that it can easily be modified and extended by the user, in order to include alternative scoring methods and new data sources. We intend to extend the system from gene-level to variant-level prioritization, by exploiting the variant data in the MSV3D database. Contact: bmhoan@gmail.com or walter.vincent.fr@gmail.com
    Downloads: 0 This Week
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