Showing 4 open source projects for "apache module"

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  • 1
    VisualGLM-6B

    VisualGLM-6B

    Chinese and English multimodal conversational language model

    VisualGLM-6B is an open-source multimodal conversational language model developed by ZhipuAI that supports both images and text in Chinese and English. It builds on the ChatGLM-6B backbone, with 6.2 billion language parameters, and incorporates a BLIP2-Qformer visual module to connect vision and language. In total, the model has 7.8 billion parameters. Trained on a large bilingual dataset — including 30 million high-quality Chinese image-text pairs from CogView and 300 million English pairs...
    Downloads: 1 This Week
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  • 2
    J-Space Cognition Suite V3.6

    J-Space Cognition Suite V3.6

    AI cognitive-enhancement Skills based on Anthropic's J-space

    J-Space Cognition Suite is a model-agnostic inference-time control system for improving deep reasoning, long-horizon work, tool use, verification, and recovery in AI agents. It is distributed as a cross-platform Skill that leaves model weights and training unchanged. The suite manages an agent's accessible working representations through selective loading instead of applying every mechanism to every task. Its fast, full, and loop modes scale from simple checks to multi-stage work requiring...
    Downloads: 1 This Week
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  • 3
    Perception Models

    Perception Models

    State-of-the-art Image & Video CLIP, Multimodal Large Language Models

    Perception Models is a state-of-the-art framework developed by Facebook Research for advanced image and video perception tasks. It introduces two primary components: the Perception Encoder (PE) for visual feature extraction and the Perception Language Model (PLM) for multimodal decoding and reasoning. The PE module is a family of vision encoders designed to excel in image and video understanding, surpassing models like SigLIP2, InternVideo2, and DINOv2 across multiple benchmarks. Meanwhile,...
    Downloads: 0 This Week
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  • 4
    Step1X-3D

    Step1X-3D

    High-Fidelity and Controllable Generation of Textured 3D Assets

    Step1X-3D is an open-source framework for generating high-fidelity textured 3D assets from scratch — both their geometry and surface textures — using modern generative AI techniques. It combines a hybrid architecture: a geometry generation stage using a VAE-DiT model to output a watertight 3D representation (e.g. TSDF surface), and a texture synthesis stage that conditions on geometry and optionally reference input (or prompts) to produce view-consistent textures using a diffusion-based...
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