Search Results for "sourceforge.net/projects/winpython/files/winpython_3.8/3.8.10.0/winpython64-3.8.10.0.7z" - Page 8

347 projects for "sourceforge.net/projects/winpython/files/winpython_3.8/3.8.10.0/winpython64-3.8.10.0.7z" with 2 filters applied:

  • Streamline Hiring with Skill Assessments Icon
    Streamline Hiring with Skill Assessments

    Say goodbye to hiring guesswork. Use Canditech’s job simulation tests to assess real-world skills and make data-driven decisions.

    Canditech offers innovative, cheat-proof skill assessments and job simulations to transform your hiring process. From technical skills to soft skills, we help you assess candidates on actual job performance. With over 500 customizable tests and powerful video interview features, you can evaluate real-world capabilities, streamline your hiring, and reduce biases. Whether you’re hiring for remote roles, mass hiring, or looking to expand your diversity pool, Canditech’s data-driven platform ensures the right candidates are chosen for the job every time.
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  • Ditto Edge Server is a lightweight standalone server for resource-constrained edge environments, based on the core Ditto Edge SDK. Icon
    Ditto Edge Server is a lightweight standalone server for resource-constrained edge environments, based on the core Ditto Edge SDK.

    With Ditto Edge Server, you can join devices as small as a Raspberry Pi to a local mesh network and synchronize data across edge environments.

    Ditto's Edge SDK is the only thing your edge devices need to ensure your application is operational in any environment, regardless of network conditions.
    Learn More
  • 1
    JiT

    JiT

    PyTorch implementation of JiT

    JiT is an open-source PyTorch implementation of a state-of-the-art image diffusion model designed around a minimalist yet powerful architecture for pixel-level generative modeling, based on the paper Back to Basics: Let Denoising Generative Models Denoise. Rather than predicting noise, JiT models directly predict clean image data, which the research suggests aligns better with the manifold structure of natural images and leads to stronger generative performance at high resolution. This...
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  • 2
    Gemma in PyTorch

    Gemma in PyTorch

    The official PyTorch implementation of Google's Gemma models

    gemma_pytorch provides the official PyTorch reference for running and fine-tuning Google’s Gemma family of open models. It includes model definitions, configuration files, and loading utilities for multiple parameter scales, enabling quick evaluation and downstream adaptation. The repository demonstrates text generation pipelines, tokenizer setup, quantization paths, and adapters for low-rank or parameter-efficient fine-tuning. Example notebooks walk through instruction tuning and evaluation so teams can benchmark and iterate rapidly. ...
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  • 3
    RAG Web UI

    RAG Web UI

    RAG Web UI is an intelligent dialogue system based on RAG

    ...It combines document retrieval with large language models to provide accurate, context-aware responses based on indexed data rather than generic model knowledge. The platform supports ingestion of multiple document formats, including PDFs, Word files, Markdown, and plain text, automatically processing and vectorizing them for efficient retrieval. It features a multi-turn conversational interface that maintains context across interactions, allowing users to engage in more natural and continuous dialogues with their data. The system is designed with a scalable architecture that separates frontend and backend components, enabling distributed deployment and efficient handling of large datasets. ...
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  • 4
    AI Notes

    AI Notes

    Curated AI engineering notes on LLMs, generative models, and tools

    ...It is designed to help software engineers quickly understand modern AI concepts, tools, and developments through structured documentation and research notes. It functions as a living knowledge base composed of numerous markdown files that organize topics such as text generation, image generation, AI infrastructure, and code generation models. These notes include observations, references, experiments, and summaries of important research and industry developments in AI. ai-notes also contains collections of prompts, curated learning materials, and categorized resources intended to help developers explore AI capabilities and practical applications.
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  • Ecwid is a hosted cloud commerce platform used by over 1.5 million merchants and offers the easiest way to add an online store to any website, social site or multiple sites simultaneously. Icon
    Ecwid is a hosted cloud commerce platform used by over 1.5 million merchants and offers the easiest way to add an online store to any website, social site or multiple sites simultaneously.

    Your free online store is just a few clicks away.

    Set up your Ecwid store once to easily sync and sell across a website, social media, marketplaces like Amazon, and live in-person. Get started with one, or try them all.
    Start Selling
  • 5
    JobWinner

    JobWinner

    Curated directory of thousands of generative AI tools by category

    AI Collection is a curated repository that aggregates a large number of generative AI applications into a single organized directory. It serves as a discovery platform where users can browse and explore AI tools across a wide range of categories and use cases. Instead of providing software code for a single application, AI Collection acts as a structured index that lists AI tools along with brief descriptions and visual previews. It organizes thousands of AI applications into dozens of...
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  • 6
    Kodezi Chronos

    Kodezi Chronos

    Kodezi Chronos is a debugging-first language model

    ...Unlike general-purpose language models that focus primarily on code generation, Chronos is built to diagnose and repair bugs by analyzing complex relationships across files within a codebase. The project introduces architectural techniques such as Adaptive Graph-Guided Retrieval, which allows the system to navigate large repositories and retrieve relevant debugging information from multiple sources. Another component, Persistent Debug Memory, allows the system to learn patterns from past debugging sessions and apply that knowledge to future problems. ...
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  • 7
    AI Deadlines

    AI Deadlines

    AI conference deadline countdowns

    ...Researchers and students use the platform to plan their paper submissions and manage academic schedules without manually tracking multiple conference announcements. The repository includes configuration files and data sources that allow contributors to add or update conferences through pull requests, enabling community-driven maintenance.
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  • 8
    pyAudioAnalysis

    pyAudioAnalysis

    Python Audio Analysis Library: Feature Extraction, Classification

    pyAudioAnalysis is an open-source Python library designed for audio signal analysis, machine learning, and music information retrieval tasks. The project provides a collection of tools that allow developers to extract meaningful features from audio files and use those features for classification, segmentation, and analysis. The library supports multiple audio processing workflows, including feature extraction from raw audio signals, training of machine learning models, and automatic audio segmentation. It also includes utilities for visualizing audio features and analyzing patterns within sound recordings, which can be useful in applications such as speech recognition, music classification, and acoustic event detection. ...
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  • 9
    Pathway AI Pipelines

    Pathway AI Pipelines

    Ready-to-run cloud templates for RAG

    ...The project provides end-to-end examples that connect live data sources to LLM workflows, enabling applications to stay synchronized with continuously changing information. It supports numerous connectors including local files, Google Drive, SharePoint, Kafka, PostgreSQL, and real-time APIs, making it suitable for enterprise data environments. The templates include built-in indexing, vector search, hybrid search, and caching capabilities that remove the need to assemble separate infrastructure components. Developers can run the applications locally or deploy them to cloud platforms using Docker with minimal setup. ...
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  • Agentic AI SRE built for Engineering and DevOps teams. Icon
    Agentic AI SRE built for Engineering and DevOps teams.

    No More Time Lost to Troubleshooting

    NeuBird AI's agentic AI SRE delivers autonomous incident resolution, helping team cut MTTR up to 90% and reclaim engineering hours lost to troubleshooting.
    Learn More
  • 10
    AI PDF Chatbot LangChain

    AI PDF Chatbot LangChain

    AI PDF chatbot agent built with LangChain & LangGraph

    AI PDF Chatbot LangChain is a full-stack template for building conversational agents that can ingest and answer questions about PDF documents. The project demonstrates how to combine LangChain and LangGraph with a vector database to enable retrieval-augmented question answering over user-provided files. It includes both frontend and backend components, making it suitable as a production starting point rather than just a minimal demo. The system parses uploaded PDFs into document chunks, generates embeddings, and stores them for semantic retrieval during chat interactions. It also supports real-time streaming responses and configurable LLM providers, giving developers flexibility in deployment. ...
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  • 11
    Neovim 99

    Neovim 99

    Neovim AI agent done right

    ...Rather than a polished end-product, this repo serves as a playground for testing, iterating, and documenting workflows that integrate AI agents directly into everyday coding tools, emphasizing rapid feedback loops, automation, and minimal friction. The project often includes configuration files, scripts, and examples that show how to coerce modern AI assistants into productive roles within editors, plugins, and terminal workflows, with a focus on “no excuses” productivity. It blends examples from Neovim, agent automation, and developer ergonomics to illustrate how AI can be baked into existing environments.
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  • 12
    video2robot

    video2robot

    End-to-end pipeline converting generative videos

    ...The pipeline supports both prompt-to-video generation using models like Veo/Sora and video upload processing, followed by human pose extraction through a 3D pose model and retargeting of that motion to robot joints using a general motion retargeting system. This workflow allows users to generate robot motion files that specify joint angles, root positions, and orientations that can be deployed on supported robot platforms (e.g., Unitree models). Video2robot includes scripts for each stage of the pipeline (generation, extraction, conversion, visualization) and can run as a CLI or through a basic web UI.
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  • 13
    Moltworker

    Moltworker

    Run OpenClaw on Cloudflare Workers

    ...With this setup, developers can host and interact with a personal AI assistant that maintains persistent conversations, integrates with chat platforms, and provides a control UI protected by Cloudflare Access. The project includes web UIs, Cloudflare configuration files, and scripts to authenticate devices, manage environment secrets, and enable optional services like persistent R2 storage for chat history.
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  • 14
    Claude Cognitive

    Claude Cognitive

    Persistent context and multi-instance coordination

    Claude Cognitive is an advanced memory and context-management extension designed to address the stateless limitations of Claude Code by giving the model a form of persistent “working memory” and multi-instance coordination. It introduces an attention-based context router that prioritizes files and content relevant to the current development discussion — tagging them as HOT, WARM, or COLD based on recency and keyword activation — so Claude Code doesn’t waste token budget rereading irrelevant code. This context routing dramatically reduces redundant token usage and accelerates large codebase interactions by focusing only on what truly matters to the current task. ...
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  • 15
    Colab-MCP

    Colab-MCP

    An MCP server for interacting with Google Colab

    Colab-MCP is an open-source Model Context Protocol server developed by Google that enables AI agents to directly interact with and control Google Colab environments programmatically, transforming Colab into a fully automated, agent-accessible workspace. Instead of relying on manual notebook usage, the system allows MCP-compatible agents to execute code, manage files, install dependencies, and orchestrate entire development workflows within Colab’s cloud infrastructure. This approach bridges the gap between local AI agents and remote high-performance compute environments, allowing users to offload heavy workloads such as machine learning training, data analysis, and dependency-heavy tasks to Colab’s GPU and TPU resources. ...
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  • 16
    Qodo Cover

    Qodo Cover

    AI tool that generates tests to improve code coverage quickly

    ...Internally, Qodo Cover uses a modular architecture that includes components for prompt generation, AI interaction, coverage analysis, and test validation. It supports scanning entire repositories to automatically detect test files, gather relevant context, and extend test suites accordingly.
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  • 17
    LEANN

    LEANN

    Local RAG engine for private multimodal knowledge search on devices

    ...By recomputing embeddings during queries and using compact graph-based indexing structures, LEANN can maintain high search accuracy while minimizing disk usage. It aims to act as a unified personal knowledge layer that connects different types of data such as documents, code, images, and other local files into a searchable context for language models.
    Downloads: 0 This Week
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  • 18
    Dagger

    Dagger

    Containerized automation engine for programmable CI/CD workflows

    Dagger is an open source automation engine designed to build, test, and deliver software in a consistent and programmable way. It enables developers to define software delivery workflows using code instead of complex shell scripts or configuration files. Dagger executes tasks inside containers, ensuring that automation runs in identical environments across local machines, CI servers, or cloud infrastructure. Dagger provides a core execution engine and system API that orchestrates containers, filesystems, secrets, repositories, and other resources needed during development pipelines. ...
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  • 19
    Semantra

    Semantra

    Multi-tool for semantic search

    Semantra is an open-source semantic search tool designed to help users explore large collections of documents by meaning rather than simple keyword matching. The software analyzes text and PDF documents stored locally and creates embeddings that allow queries to retrieve results based on conceptual similarity. It is primarily intended for individuals who need to extract insights from large document collections, including researchers, journalists, students, and historians. The system runs...
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  • 20
    deepjazz

    deepjazz

    Deep learning driven jazz generation using Keras & Theano

    deepjazz is a deep learning project that generates jazz music using recurrent neural networks trained on MIDI files. The repository demonstrates how machine learning can learn musical structure and produce original compositions. It uses the Keras and Theano libraries to build a two-layer Long Short-Term Memory network capable of learning temporal patterns in music. The system analyzes musical sequences from an input MIDI file and then generates new musical notes that follow similar stylistic patterns. ...
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  • 21
    seq2seq-couplet

    seq2seq-couplet

    Play couplet with seq2seq model

    ...It also supports serving the trained model through a web service, allowing users to interact with the system after training is complete. In addition to local execution, the project includes Docker files, which make it easier to package and deploy the application in a more reproducible way. The repository also points users to an external dataset source and documents vocabulary formatting requirements for custom datasets, showing that it is meant for both experimentation and extension.
    Downloads: 0 This Week
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  • 22
    TigerBot

    TigerBot

    TigerBot: A multi-language multi-task LLM

    ...The project provides both base models and chat-optimized variants that can be used for dialogue systems, question answering, and general language understanding tasks. In addition to model weights, the repository includes training scripts, inference tools, and configuration files that allow researchers and developers to reproduce experiments or fine-tune the models for specific applications.
    Downloads: 0 This Week
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  • 23
    LLM Workflow Engine

    LLM Workflow Engine

    Power CLI and Workflow manager for LLMs (core package)

    ...Instead of focusing solely on chat interactions, the system is built to embed LLM calls into larger automation pipelines where model outputs can drive decision making or trigger additional processes. Developers can construct structured workflows using configuration files and integrate them with tools such as Ansible playbooks or custom scripts to automate complex tasks. The engine supports multiple AI providers through a plugin architecture, allowing connections to services like OpenAI, Hugging Face, Cohere, or other compatible APIs.
    Downloads: 0 This Week
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  • 24
    MemFree

    MemFree

    Hybrid AI Search Engine & AI Page Generator

    memfree is an open source hybrid AI search engine and page generation platform designed to help users retrieve information from both personal knowledge bases and the public web through a unified interface. The project combines retrieval-augmented search with AI summarization to deliver concise answers instead of forcing users to manually sift through multiple sources. It supports multiple AI models and search providers, enabling flexible configuration depending on cost, performance, or...
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  • 25
    LLM TLDR

    LLM TLDR

    95% token savings. 155x faster queries. 16 languages

    LLM TLDR is a tool that leverages large language models (LLMs) to generate concise, coherent summaries (TL;DRs) of long documents, articles, or text files, helping users quickly understand large amounts of content without reading every word. It integrates with LLM APIs to handle input texts of varying lengths and complexity, applying techniques like chunking, context management, and multi-pass summarization to preserve accuracy even when the source is very large. The system supports both extractive and abstractive summarization styles so that users can choose whether they want condensed highlights or a more narrative paraphrase of key ideas. ...
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