Showing 642 open source projects for "python code editor"

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  • 1
    Brainiac, Is C/C++ Libraries, Programs, And Python, And Lua Scripts For Neural Networking And Genetic Programming, In An Attempt To Create A "Glue-It-All-Together" Project, Striving Towards General Artificial Intelligence
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  • 2
    Source code from the book "Artificial Intelligence for Computer Games: An Introduction" by John Funge.
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  • 3
    RL-Glue has moved to google code. Please see: http://code.google.com/p/rl-glue/
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  • 4
    Multi Agent based distributed application. The code can be processed over multiple common machines with fault-tolerance. It is designed to distributively run any Python's script, which can be applied to a given input data set.
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  • 5
    Mental is a neural network engine implemented in pure Python. Design goals are easy-to-read source code, completeness, and ease of use. Presently implements feed-forward, back-propagation networks. Intended primarily for instructional use.
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  • 6
    Pangaea will be a robust and feature filled game engine built using Allegro (http://alleg.sourceforge.net) It will be similar to Final Fantasy 1-3, etc., complete with map editor/world builder.
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  • 7
    The Python Genetic Programming Project implements a Genetic Programming System a la J Koza in Python.
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  • 8
    ** IMPORTANT NOTICE ** 10 Feb 2006 Code is being moved to the SMI subversion repository (http://smi-protege.stanford.edu/svn/owl/trunk/) Project will continue to be open source. ProtegeOWL info at: http://protege.stanford.edu/overview/protege-owl.html
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  • 9
    Mellum-4b-base

    Mellum-4b-base

    JetBrains’ 4B parameter code model for completions

    Mellum-4b-base is JetBrains’ first open-source large language model designed and optimized for code-related tasks. Built with 4 billion parameters and a LLaMA-style architecture, it was trained on over 4.2 trillion tokens across multiple programming languages, including datasets such as The Stack, StarCoder, and CommitPack. With a context window of 8,192 tokens, it excels at code completion, fill-in-the-middle tasks, and intelligent code suggestions for professional developer tools and IDEs. ...
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  • 10
    Generic engine to filter information. We wish to show that the power of expression of a filter makes it possible to appreciably reduce the size of the code necessary to extract information and that it is possible in Python.
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  • 11
    Some NLP experiments starting with a tokenization attempt in Python. The code tokenite.py reads a text file "blog1.txt" and tries to tokenize it. The code doesnot work as is, but is almost on the verge of working. Any suggestions will be greatly appreciated. I define a class called text and define methods inside it. The method count defines a generator which I use in the method named t_tok. But if you look closely at 66 to 72 you will see that I am modifying the outer limit of the for loop while in the loop. ...
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  • 12
    NewsNotFound

    NewsNotFound

    This is the entire source code for NewsNotFound's article gen process

    Our mission is to lead the way in AI journalism by providing completely neutral and unbiased news articles that can be governed by the public. NewsNotFound is a news website located at https://newsnotfound.com. We want to build the most unbiased news platform on the internet.
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  • 13
    gpt-oss-20b

    gpt-oss-20b

    OpenAI’s compact 20B open model for fast, agentic, and local use

    GPT-OSS-20B is OpenAI’s smaller, open-weight language model optimized for low-latency, agentic tasks, and local deployment. With 21B total parameters and 3.6B active parameters (MoE), it fits within 16GB of memory thanks to native MXFP4 quantization. Designed for high-performance reasoning, it supports Harmony response format, function calling, web browsing, and code execution. Like its larger sibling (gpt-oss-120b), it offers adjustable reasoning depth and full chain-of-thought visibility...
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  • 14
    Monk Computer Vision

    Monk Computer Vision

    A low code unified framework for computer vision and deep learning

    Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers. There are three libraries in this opensource set. - Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms. - Monk Object Detection -...
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  • 15

    text_summurization_abstractive_methods

    Multiple implementations for abstractive text summurization

    This repo is built to collect multiple implementations for abstractive approaches to address text summarization it is built to simply run on google colab , in one notebook so you would only need an internet connection to run these examples without the need to have a powerful machine , so all the code examples would be in a jupyter format , and you don't have to download data to your device as we connect these jupyter notebooks to google drive
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  • 16
    One Horizon

    One Horizon

    Increase productivity & insights for software development teams

    Did you know software developers only spend 40% of their time writing code? A lot is wasted in reporting to their manager, inefficient daily standups, and other miscommunication. With One Horizon, we connect to tools devs already use like GitHub, Slack, MCP (Cursor, Claude, etc.), Jira/Linear and Google Calendar. By combining the context across these tools, we can generate a daily recap of what each dev did yesterday, what they can work on today/tomorrow (just top priorities, not the full...
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  • 17
    OpenVLA 7B

    OpenVLA 7B

    Vision-language-action model for robot control via images and text

    OpenVLA 7B is a multimodal vision-language-action model trained on 970,000 robot manipulation episodes from the Open X-Embodiment dataset. It takes camera images and natural language instructions as input and outputs normalized 7-DoF robot actions, enabling control of multiple robot types across various domains. Built on top of LLaMA-2 and DINOv2/SigLIP visual backbones, it allows both zero-shot inference for known robot setups and parameter-efficient fine-tuning for new domains. The model...
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