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2 dépôts

Awesome GitHub RepositoriesAI Model Execution

Running machine learning models within a live Android application environment.

Distinct from Android Runtime Execution: Distinct from general Android runtime execution by focusing specifically on AI model inference and tokenization.

Explore 2 awesome GitHub repositories matching mobile development · AI Model Execution. Refine with filters or upvote what's useful.

Awesome AI Model Execution GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • firebase/genkitAvatar de firebase

    firebase/genkit

    6,121Voir sur GitHub↗

    Genkit is an open-source framework for building AI-powered applications. It provides a unified interface for connecting to hundreds of generative AI models from multiple providers, enabling text, image, audio, and video generation through a single API. The framework structures multi-step AI interactions—including chat, retrieval-augmented generation, tool use, and agentic workflows—as composable, traceable flows with built-in streaming and state management. The framework distinguishes itself through a comprehensive developer toolkit that includes a command-line interface and a local developer

    Provides a flow-based execution model for composable, traceable AI workflows with streaming and state management.

    TypeScript
    Voir sur GitHub↗6,121
  • pytorch/executorchAvatar de pytorch

    pytorch/executorch

    4,296Voir sur GitHub↗

    ExecuTorch is a lightweight C++ runtime for deploying PyTorch models on mobile, embedded, and edge hardware. It provides an ahead-of-time compilation pipeline that exports, quantizes, and lowers model graphs into compact serialized programs, then executes them through a minimal runtime with hardware acceleration and on-device large language model inference capabilities. The project distinguishes itself through a hardware accelerator delegate system that partitions model subgraphs and offloads computation to specialized backends including NPUs, GPUs, and DSPs from Apple, Arm, Intel, MediaTek,

    Loads serialized programs and runs inference with a lightweight C++ runtime on edge devices.

    Pythondeep-learningembeddedgpu
    Voir sur GitHub↗4,296
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  2. Mobile Development
  3. Android Runtime Execution
  4. AI Model Execution

Explorer les sous-tags

  • Composable Workflow ExecutionsExecutes AI workflows as composable, traceable functions with streaming and state management built into the runtime. **Distinct from AI Model Execution:** Distinct from AI Model Execution: focuses on composable workflow orchestration with streaming and state, not just running a model.