Showing 13 open source projects for "text compare"

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  • 1
    Google AI Edge Gallery

    Google AI Edge Gallery

    A gallery that showcases on-device ML/GenAI use cases

    Gallery is a curated collection of on-device machine learning examples, demo apps, and model artifacts designed to help developers experiment with and deploy ML at the edge. The project bundles runnable samples that show how to run TensorFlow Lite/Edge TPU models (and similar lightweight runtimes) on mobile and embedded platforms, demonstrating common tasks like image classification, object detection, audio recognition, and pose estimation. Each sample is intended to be both a learning aid...
    Downloads: 1,601 This Week
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  • 2
    Learning Interpretability Tool

    Learning Interpretability Tool

    Interactively analyze ML models to understand their behavior

    The Learning Interpretability Tool (LIT, formerly known as the Language Interpretability Tool) is a visual, interactive ML model-understanding tool that supports text, image, and tabular data. It can be run as a standalone server, or inside of notebook environments such as Colab, Jupyter, and Google Cloud Vertex AI notebooks.
    Downloads: 5 This Week
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  • 3
    dLLM

    dLLM

    dLLM: Simple Diffusion Language Modeling

    dLLM is an open-source framework designed to simplify the development, training, and evaluation of diffusion-based large language models. Unlike traditional autoregressive models that generate text sequentially token by token, diffusion language models generate text through an iterative denoising process that refines masked tokens over multiple steps. This approach allows models to reason over the entire sequence simultaneously and potentially produce more coherent outputs with bidirectional context. The project provides an integrated pipeline that standardizes how diffusion language models are trained, evaluated, and deployed, helping researchers reproduce experiments and compare results more easily. ...
    Downloads: 0 This Week
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  • 4
    Weights and Biases

    Weights and Biases

    Tool for visualizing and tracking your machine learning experiments

    Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. Quickly identify model regressions. Use W&B to visualize results in real time, all in a central dashboard. Focus on the interesting ML. Spend less time manually tracking results in spreadsheets and text files. Capture dataset versions with W&B Artifacts to identify how changing data affects your resulting models. Reproduce any model, with saved...
    Downloads: 12 This Week
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  • 5
    Lingvo

    Lingvo

    Framework for building neural networks

    Lingvo is a TensorFlow based framework focused on building and training sequence models, especially for language and speech tasks. It was originally developed for internal research and later open sourced to support reproducible experiments and shared model implementations. The framework provides a structured way to define models, input pipelines, and training configurations using a common interface for layers, which encourages reuse across different tasks. It has been used to implement state...
    Downloads: 0 This Week
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  • 6
    Canopy

    Canopy

    Retrieval Augmented Generation (RAG) framework

    ...The framework includes a built-in server and command-line interface that allow users to experiment with RAG pipelines and compare outputs between retrieval-augmented responses and standard LLM responses.
    Downloads: 6 This Week
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  • 7
    State of Open Source AI

    State of Open Source AI

    Clarity in the current fast-paced mess of Open Source innovation

    ...It acts as both a snapshot and a guide: readers can see what’s “hot now” in open AI infrastructure, what open licensing or governance issues are emerging, how deployment options compare, and what gaps remain. Because the AI domain moves quickly, part of the aim is to make the content maintainable and updateable by the community. The structure includes chapters or sections about model formats, evaluation benchmarks, hardware/backends, MLOps systems, alignment and safety issues, and open datasets. The repository contains the text (in Markdown or similar), configuration for build or publishing (static site or e-book), and contributor guidelines.
    Downloads: 0 This Week
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  • 8
    textacy

    textacy

    NLP, before and after spaCy

    textacy is a Python library for performing a variety of natural language processing (NLP) tasks, built on the high-performance spaCy library. With the fundamentals, tokenization, part-of-speech tagging, dependency parsing, etc., delegated to another library, textacy focuses primarily on the tasks that come before and follow after.
    Downloads: 0 This Week
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  • 9
    T81 558

    T81 558

    Applications of Deep Neural Networks

    Deep learning is a group of exciting new technologies for neural networks. Through a combination of advanced training techniques and neural network architectural components, it is now possible to create neural networks that can handle tabular data, images, text, and audio as both input and output. Deep learning allows a neural network to learn hierarchies of information in a way that is like the function of the human brain. This course will introduce the student to classic neural network...
    Downloads: 0 This Week
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  • 10
    Tensor2Tensor

    Tensor2Tensor

    Library of deep learning models and datasets

    Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and...
    Downloads: 0 This Week
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  • 11

    Lords Mobile Player Statistics

    Compare yourself with others by analyzing Lords Mobile Screenshots

    Lords Mobile Player Statistics (or short Lords Mobile Stats) is a Windows application that allows you to parse Lords Mobile Screenshots to extract player statistics of yourself and other players. After extracting the data you can compare players and view the data as a large sortable table. You can also export the results as text file or render the table as an image (for sharing with your guild for example). This project is still in a early development stage, please read the Wiki (see menu above) for details about what is working and what is not. There are still many features on the todo list for future release. ...
    Downloads: 0 This Week
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  • 12

    dbacl - digramic Bayesian classifier

    commandline multiclass email and text filter

    dbacl is a general purpose digramic Bayesian text classifier. It can learn text documents you provide, and then compare new input with the learned categories. It can be used for spam filtering, or within your own shell scripts. Sometimes it plays che
    Downloads: 3 This Week
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  • 13
    Optex Analyzer is a software to analyze and compare algorithms to solve approximately optimization problems. It has a GUI that allows select a set of input files containing raw algorithm results. The analysis is shown with tables and charts.
    Downloads: 0 This Week
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