Showing 8 open source projects for "skippy-mesh"

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  • 1
    GPT-NeoX

    GPT-NeoX

    Implementation of model parallel autoregressive transformers on GPUs

    ... recommend Mesh Transformer JAX. If you are not looking to train models with billions of parameters from scratch, this is likely the wrong library to use. For generic inference needs, we recommend you use the Hugging Face transformers library instead which supports GPT-NeoX models.
    Downloads: 9 This Week
    Last Update:
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  • 2
    Stable-Dreamfusion

    Stable-Dreamfusion

    Text-to-3D & Image-to-3D & Mesh Exportation with NeRF + Diffusion

    A pytorch implementation of the text-to-3D model Dreamfusion, powered by the Stable Diffusion text-to-2D model. This project is a work-in-progress and contains lots of differences from the paper. The current generation quality cannot match the results from the original paper, and many prompts still fail badly! Since the Imagen model is not publicly available, we use Stable Diffusion to replace it (implementation from diffusers). Different from Imagen, Stable-Diffusion is a latent diffusion...
    Downloads: 2 This Week
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  • 3
    aigc

    aigc

    An e-book about the real-world application of LLM

    "Building Large Language Model Applications: Application Development and Architecture Design" is an open source e-book about the real-world application of LLM. It introduces the basics and applications of large language models, as well as how to build your own models. These include writing, developing, and managing prompts, exploring what the best large language models can bring, and pattern and architecture design for LLM application development.
    Downloads: 1 This Week
    Last Update:
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  • 4
    DocArray

    DocArray

    The data structure for multimodal data

    DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. Data...
    Downloads: 0 This Week
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  • 5
    Jina

    Jina

    Build cross-modal and multimodal applications on the cloud

    Jina is a framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer. Build applications that deliver fresh insights from multiple data types such as text, image, audio, video, 3D mesh, PDF with Jina AI’s DocArray. Polyglot gateway that supports gRPC, Websockets, HTTP...
    Downloads: 0 This Week
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  • 6
    GPT Neo

    GPT Neo

    An implementation of model parallel GPT-2 and GPT-3-style models

    An implementation of model & data parallel GPT3-like models using the mesh-tensorflow library. If you're just here to play with our pre-trained models, we strongly recommend you try out the HuggingFace Transformer integration. Training and inference is officially supported on TPU and should work on GPU as well. This repository will be (mostly) archived as we move focus to our GPU-specific repo, GPT-NeoX. NB, while neo can technically run a training step at 200B+ parameters, it is very...
    Downloads: 17 This Week
    Last Update:
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  • 7
    NOMAD is a C++ code that implements the MADS algorithm (Mesh Adaptive Direct Search) for difficult blackbox optimization problems. Such problems occur when the functions to optimize are costly computer simulations with no derivatives.
    Downloads: 8 This Week
    Last Update:
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  • 8
    Neural Mesh
    Neural Mesh is a purely PHP, fast, easy Neural Network Manager, Administrator and Framework. It allows you to integrate Artificial Intelligence into your applications, quickly and easily, no matter what your experience.
    Downloads: 0 This Week
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