Showing 10 open source projects for "core"

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  • 1
    Flowise

    Flowise

    Drag & drop UI to build your customized LLM flow

    Open source UI visual tool to build your customized LLM flow using LangchainJS, written in Node Typescript/Javascript. Conversational agent for a chat model which utilizes chat-specific prompts and buffer memory. Open source is the core of Flowise, and it will always be free for commercial and personal usage. Flowise support different environment variables to configure your instance. You can specify the following variables in the .env file inside the packages/server folder.
    Downloads: 11 This Week
    Last Update:
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  • 2
    bert4torch

    bert4torch

    An elegent pytorch implement of transformers

    An elegant PyTorch implement of transformers.
    Downloads: 0 This Week
    Last Update:
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  • 3
    Quivr

    Quivr

    Your Second Brain supercharged by Generative AI

    Quivr, your second brain, utilizes the power of GenerativeAI to store and retrieve unstructured information. Think of it as Obsidian, but turbocharged with AI capabilities.
    Downloads: 0 This Week
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  • 4
    LLamaSharp

    LLamaSharp

    C#/.NET binding of llama.cpp, including LLaMa/GPT model inference

    The C#/.NET binding of llama.cpp. It provides APIs to infer the LLaMa Models and deploy it on the local environment. It works on both Windows, Linux and MAC without the requirement for compiling llama.cpp yourself. Its performance is close to llama.cpp. Furthermore, it provides integrations with other projects such as BotSharp to provide higher-level applications and UI.
    Downloads: 0 This Week
    Last Update:
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  • Repair-CRM Icon
    Repair-CRM

    For small companies that repair and maintenance customer machines

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  • 5
    llm.c

    llm.c

    LLM training in simple, raw C/CUDA

    llm.c is a minimalist, systems-level implementation of a small transformer-based language model in C that prioritizes clarity and educational value. By stripping away heavy frameworks, it exposes the core math and memory flows of embeddings, attention, and feed-forward layers. The code illustrates how to wire forward passes, losses, and simple training or inference loops with direct control over arrays and buffers. Its compact design makes it easy to trace execution, profile hotspots, and understand the cost of each operation. Portability is a goal: it aims to compile with common toolchains and run on modest hardware for small experiments. ...
    Downloads: 0 This Week
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  • 6
    NeMo Curator

    NeMo Curator

    Scalable data pre processing and curation toolkit for LLMs

    ...The library provides a customizable and modular interface, simplifying pipeline expansion and accelerating model convergence through the preparation of high-quality tokens. At the core of the NeMo Curator is the DocumentDataset which serves as the the main dataset class. It acts as a straightforward wrapper around a Dask DataFrame. The Python library offers easy-to-use methods for expanding the functionality of your curation pipeline while eliminating scalability concerns.
    Downloads: 0 This Week
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  • 7
    ML Ferret

    ML Ferret

    Refer and Ground Anything Anywhere at Any Granularity

    Ferret is Apple’s end-to-end multimodal large language model designed specifically for flexible referring and grounding: it can understand references of any granularity (boxes, points, free-form regions) and then ground open-vocabulary descriptions back onto the image. The core idea is a hybrid region representation that mixes discrete coordinates with continuous visual features, so the model can fluidly handle “any-form” referring while maintaining precise spatial localization. The repo presents the vision-language pipeline, model assets, and paper resources that show how Ferret answers questions, follows instructions, and returns grounded outputs rather than just text. ...
    Downloads: 0 This Week
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  • 8
    MiniMax-01

    MiniMax-01

    Large-language-model & vision-language-model based on Linear Attention

    ...It has 456 billion total parameters with 45.9 billion activated per token and is trained with advanced parallel strategies such as LASP+, varlen ring attention, and Expert Tensor Parallelism, enabling a training context of 1 million tokens and up to 4 million tokens at inference. MiniMax-VL-01 extends this core by adding a 303M-parameter Vision Transformer and a two-layer MLP projector in a ViT–MLP–LLM framework, allowing the model to process images at dynamic resolutions up to 2016×2016.
    Downloads: 1 This Week
    Last Update:
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  • 9
    LLaMA

    LLaMA

    Inference code for Llama models

    ...Tokenizer utilities, download scripts, shell helpers to fetch model weights with correct licensing/permissions. Includes example scripts for chat completions and text completions to show how to call the models in code. This repo is a core piece of the Llama model infrastructure, used by researchers and developers to run LLaMA models locally or in their infrastructure. It is meant for inference (not training from scratch) and connects with aspects like model cards, responsible use, licensing, etc.
    Downloads: 1 This Week
    Last Update:
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  • 10
    Chameleon LLM

    Chameleon LLM

    Codes for "Chameleon: Plug-and-Play Compositional Reasoning

    ...By integrating various tools such as vision models, web search engines, Python functions, and rule-based modules, Chameleon delivers more accurate, up-to-date, and precise responses, making it a game-changer in the natural language processing landscape. With GPT-4 at its core, Chameleon has showcased exceptional improvements in accuracy on benchmark tasks, outperforming competitors and setting new industry standards.
    Downloads: 0 This Week
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