11 projects for "python samples" with 2 filters applied:

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  • 1
    GPT-2 Output Dataset

    GPT-2 Output Dataset

    Dataset of GPT-2 outputs for research in detection, biases, and more

    The GPT-2 Output Dataset is a large collection of model-generated text, released by OpenAI alongside the GPT-2 research paper to study the behaviors and limitations of large language models. It contains 250,000 samples of GPT-2 outputs, generated with different sampling strategies such as top-k truncation, to highlight the diversity and quality of model completions. The dataset also includes corresponding human-written text for comparison, enabling researchers to explore methods for...
    Downloads: 6 This Week
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  • 2
    Generative AI Docs

    Generative AI Docs

    Documentation for Google's Gen AI site - including Gemini API & Gemma

    Generative AI Docs is Google’s official documentation repository for Gemini, Vertex AI, and related generative AI APIs. It contains guides, API references, and examples for developers building applications using Google’s large language models, text-to-image models, embeddings, and multimodal capabilities. The repository includes markdown source files that power the Google AI developer documentation site, as well as sample code snippets in Python, JavaScript, and other languages that...
    Downloads: 2 This Week
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  • 3
    MobileCLIP

    MobileCLIP

    Implementation of "MobileCLIP" CVPR 2024

    MobileCLIP is a family of efficient image-text embedding models designed for real-time, on-device retrieval and zero-shot classification. The repo provides training, inference, and evaluation code for MobileCLIP models trained on DataCompDR, and for newer MobileCLIP2 models trained on DFNDR. It includes an iOS demo app and Core ML artifacts to showcase practical, offline photo search and classification on iPhone-class hardware. Project notes highlight latency/accuracy trade-offs, with...
    Downloads: 0 This Week
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  • 4
    Flow Matching

    Flow Matching

    A PyTorch library for implementing flow matching algorithms

    flow_matching is a PyTorch library implementing flow matching algorithms in both continuous and discrete settings, enabling generative modeling via matching vector fields rather than diffusion. The underlying idea is to parameterize a flow (a time-dependent vector field) that transports samples from a simple base distribution to a target distribution, and train via matching of flows without requiring score estimation or noisy corruption—this can lead to more efficient or stable generative...
    Downloads: 0 This Week
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    Free and Open Source HR Software

    OrangeHRM provides a world-class HRIS experience and offers everything you and your team need to be that HR hero you know that you are.

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  • 5
    AnimateDiff

    AnimateDiff

    Plug-n-play module turning text-to-image models into animation

    AnimateDiff is an open-source project designed to enhance text-to-image diffusion models by adding animation capabilities. It allows users to turn static images generated by popular text-to-image models into animated sequences without requiring additional model training. This plug-and-play tool is compatible with a wide range of community models and facilitates the generation of animation directly from pre-existing text-to-image models. It supports various configurations to create animations...
    Downloads: 16 This Week
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  • 6
    Consistency Models

    Consistency Models

    Official repo for consistency models

    consistency_models is the repository for Consistency Models, a new family of generative models introduced by OpenAI that aim to generate high-quality samples by mapping noise directly into data — circumventing the need for lengthy diffusion chains. It builds on and extends diffusion model frameworks (e.g. based on the guided-diffusion codebase), adding techniques like consistency distillation and consistency training to enable fast, often one-step, sample generation. The repo is implemented...
    Downloads: 0 This Week
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  • 7
    PRM800K

    PRM800K

    800,000 step-level correctness labels on LLM solutions to MATH problem

    PRM800K is a process supervision dataset accompanying the paper Let’s Verify Step by Step, providing 800,000 step-level correctness labels on model-generated solutions to problems from the MATH dataset. The repository releases the raw labels and the labeler instructions used in two project phases, enabling researchers to study how human raters graded intermediate reasoning. Data are stored as newline-delimited JSONL files tracked with Git LFS, where each line is a full solution sample that...
    Downloads: 4 This Week
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  • 8
    ChatGPT Plugins Collection

    ChatGPT Plugins Collection

    An unofficial collection of Plugins for ChatGPT

    ChatGPT-Plugins-Collection is a community-driven repository that gathers examples and resources for building, testing, and experimenting with ChatGPT plugins. The collection provides a variety of plugin implementations that showcase different use cases, helping developers learn how to extend ChatGPT’s functionality. It is designed to serve both as a learning resource for beginners and a reference point for more experienced developers. By centralizing community contributions, the repository...
    Downloads: 9 This Week
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  • 9
    Guided Diffusion

    Guided Diffusion

    Codebase for Diffusion Models Beat GANS on Image Synthesis

    The guided-diffusion repository is centered on diffusion models for image synthesis, with a focus on classifier guidance and improvements over earlier diffusion frameworks. It is derived from OpenAI’s improved-diffusion work, enhanced to include guided generation where a classifier (or other guidance mechanism) can steer sampling toward desired classes or attributes. The code provides model definitions (UNet, diffusion schedules), sampling and training scripts, and utilities for guidance and...
    Downloads: 0 This Week
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    Business Automation Software for SMBs

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  • 10

    Training Image Operators from Samples

    Tools to train Image Operators automatically from a set of samples.

    TRIOS - Training Image Operators from Samples is a set of tools to bring Image Processing closer to scientists in general. It is capable of estimating an operator between two images using only pairs of samples that contain an input image and the desired output. The operator is saved to a file and can be applied to any image.
    Downloads: 0 This Week
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  • 11
    This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
    Downloads: 0 This Week
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