Showing 235 open source projects for "auto code generation"

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  • 1
    gpt2-client

    gpt2-client

    Easy-to-use TensorFlow Wrapper for GPT-2 117M, 345M, 774M, etc.

    ...Finally, gpt2-client is a wrapper around the original gpt-2 repository that features the same functionality but with more accessiblity, comprehensibility, and utilty. You can play around with all four GPT-2 models in less than five lines of code. Install client via pip. The generation options are highly flexible. You can mix and match based on what kind of text you need generated, be it multiple chunks or one at a time with prompts.
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  • 2
    TGAN

    TGAN

    Generative adversarial training for generating synthetic tabular data

    We are happy to announce that our new model for synthetic data called CTGAN is open-sourced. The new model is simpler and gives better performance on many datasets. TGAN is a tabular data synthesizer. It can generate fully synthetic data from real data. Currently, TGAN can generate numerical columns and categorical columns. TGAN has been developed and runs on Python 3.5, 3.6 and 3.7. Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid...
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  • 3
    Tensorpack

    Tensorpack

    A Neural Net Training Interface on TensorFlow, with focus on speed

    ...Tensorpack squeezes the most performance out of pure Python with various auto parallelization strategies. There are too many symbolic function wrappers already. Tensorpack includes only a few common layers. You can use any TF symbolic functions inside Tensorpack.
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  • 4
    SG2Im

    SG2Im

    Code for "Image Generation from Scene Graphs", Johnson et al, CVPR 201

    sg2im is a research codebase that learns to synthesize images from scene graphs—structured descriptions of objects and their relationships. Instead of conditioning on free-form text alone, it leverages graph structure to control layout and interactions, generating scenes that respect constraints like “person left of dog” or “cup on table.” The pipeline typically predicts object layouts (bounding boxes and masks) from the graph, then renders a realistic image conditioned on those layouts....
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  • 5

    ANGie

    Alice Next Generation (internet entity)

    An AIML based chat bot building on the original Alice AIML 1.0.1 set produced by Dr. Wallace and the ALICE AI Foundation and the PyAIML code base written by Cort Stratton, the ANGie project incorporates additional AIML sets, adds its own AIML to the set, adds new AIML tags and additional code to provide more dynamic responses and more logical case-based-reasoning. Reading through most AIML sets it seems like the authors' intention was to have a response to every input that a bot has ever...
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  • 6
    auto_ml

    auto_ml

    Automated machine learning for analytics & production

    auto_ml is designed for production. Here's an example that includes serializing and loading the trained model, then getting predictions on single dictionaries, roughly the process you'd likely follow to deploy the trained model. Before you go any further, try running the code. Load up some data (either a DataFrame, or a list of dictionaries, where each dictionary is a row of data). Make a column_descriptions dictionary that tells us which attribute name in each row represents the value we’re...
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  • 7
    Seq2Seq Chatbot

    Seq2Seq Chatbot

    Chatbot in 200 lines of code using TensorLayer

    Seq2Seq Chatbot is an implementation of a sequence-to-sequence chatbot model using TensorLayer, demonstrating how to build conversational agents with minimal code.
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  • 8
    RoboComp
    RoboComp is a robotics framework providing a set of open-source, distributed, real-time robotic and artificial vision software components and the necessary tools to create and manage them.
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  • 9

    mullpy

    Multilabel-learning library built on python

    Mullpy is a machine-learning library that mainly aim to solve multi-label problems. It is classifier independent, has many ensemble capabilities (diversity methods like bagging, random subspaces, etc.) and automated results presentation (Excel, images as ROC or class-separated info, etc.). It is fully configurable. At the moment supports Neural Networks and classifiers defined in files. It is working on python3.3.
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  • 10
    pyIRDG

    pyIRDG

    IMDb Relational Dataset Generator

    pyIRDG is a program written in Python to generate relational datasets in Prolog format. It uses data from the Internet Movie Database in combination with IMDbPY as backend. A graphical user interface written in pyQt allows the user to link multiple entities together as model for the generation process. The big four entities are Title, Person, Company and Character. Many attributes can be chosen for adding to the output .pl file. Three types of constraints on attributes are available to limit...
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