Showing 4 open source projects for "tiny"

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  • 1
    tiny-llm

    tiny-llm

    A course of learning LLM inference serving on Apple Silicon

    tiny-llm is an educational open-source project designed to teach system engineers how large language model inference and serving systems work by building them from scratch. The project is structured as a guided course that walks developers through the process of implementing the core components required to run a modern language model, including attention mechanisms, token generation, and optimization techniques.
    Downloads: 1 This Week
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  • 2
    SillyTavern

    SillyTavern

    LLM Frontend for Power Users

    Mobile-friendly, Multi-API (KoboldAI/CPP, Horde, NovelAI, Ooba, OpenAI, OpenRouter, Claude, Scale), VN-like Waifu Mode, Horde SD, System TTS, WorldInfo (lorebooks), customizable UI, auto-translate, and more prompt options than you'd ever want or need. Optional Extras server for more SD/TTS options + ChromaDB/Summarize. SillyTavern is a user interface you can install on your computer (and Android phones) that allows you to interact with text generation AIs and chat/roleplay with characters...
    Downloads: 384 This Week
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  • 3
    LLMs-from-scratch

    LLMs-from-scratch

    Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

    ...The repository favors clear Python and NumPy or PyTorch implementations that can be run and modified without heavyweight frameworks obscuring the logic. Chapters and notebooks progress from tiny toy models to more capable transformer stacks, including sampling strategies and evaluation hooks. The focus is on readability, correctness, and experimentation, making it ideal for students and practitioners transitioning from theory to working systems. By the end, you have a grounded sense of how data pipelines, optimization, and inference interact to produce fluent text.
    Downloads: 1 This Week
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  • 4
    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...
    Downloads: 0 This Week
    Last Update:
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