Showing 32 open source projects for "ollama"

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  • 1
    GNNPCSAFT Chat

    GNNPCSAFT Chat

    Chatbot with GNNPCSAFT

    The GNNPCSAFT Chat is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, you can chat with LLM models (Gemini or Ollama) with GNNPCSAFT tools, allowing you to ask questions about the PC-SAFT parameters of various compounds, predict thermodynamic properties, and get insights into the GNNPCSAFT's performance.
    Downloads: 2 This Week
    Last Update:
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  • 2
    StudioOllamaUI

    StudioOllamaUI

    StudioOllamaUI is a local, portable interface for Ollama

    StudioOllamaUI: Portable .The easiest way to run local AI Do you want to use AI but don't know what Docker is? Does the terminal scare you? StudioOllamaUI is for you. Zero Installation: Works on a fresh Windows installation. No Python, no libraries, no drama. 100% Portable: Just like a portable browser. Unzip, run, and that's it. It doesn't clutter your registry or leave traces on your disk. AI for Everyone: No expensive GPU? No problem. Optimized to run smoothly on your CPU...
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    Downloads: 27 This Week
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  • 3
    CodinIT.dev

    CodinIT.dev

    Free, local, open-source AI app builder

    ...Deep Supabase integration means you can create UI and backend logic in one cohesive environment, while the model-agnostic architecture lets you connect to any AI, whether cloud-based (Gemini 3 Pro, GPT-5, Claude Sonnet 4.5) or local via Ollama, so you’re never locked in. All source code remains on your device and integrates seamlessly with your preferred IDE. A natural-language API enables powerful data queries and updates, automating tasks without leaving the chat interface. By running entirely locally, CodinIT.dev delivers maximum privacy, minimal latency, and smooth developer experiences free from cloud-based inconsistencies.
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    Downloads: 15 This Week
    Last Update:
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  • 4
    Shinkai: Local AI Agents

    Shinkai: Local AI Agents

    Shinkai allows you to create advanced AI (local) agents effortlessly

    Shinkai is a free, open-source AI platform that lets anyone create powerful AI agents without coding. These agents can collaborate with each other, handle complex tasks, and operate in decentralized crypto environments. Key Features: - No-Code Agent Creation - Build specialized agents (trading bots, sentiment trackers, etc.) with simple descriptions - Multi-Agent Collaboration - Agents work together to solve complex problems - Crypto Integration - Built-in support for decentralized...
    Downloads: 4 This Week
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  • 5

    Infinite Sides

    Infinite Craft but in Pyside6 and Python with local LLM

    Infinite Craft but in Pyside6 and Python with local LLM (llama2 & others) using Ollama that also lets you create your own crafting game based on any topic Customize the game any way you like in the settings.
    Downloads: 0 This Week
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  • 6
    gpt-oss-20b

    gpt-oss-20b

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

    ...Like its larger sibling (gpt-oss-120b), it offers adjustable reasoning depth and full chain-of-thought visibility for better interpretability. It’s released under a permissive Apache 2.0 license, allowing unrestricted commercial and research use. GPT-OSS-20B is compatible with Transformers, vLLM, Ollama, PyTorch, and other tools. It is ideal for developers building lightweight AI agents or experimenting with fine-tuning on consumer-grade hardware.
    Downloads: 0 This Week
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  • 7
    Mellum-4b-base

    Mellum-4b-base

    JetBrains’ 4B parameter code model for completions

    ...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. The model is efficient for both cloud inference with vLLM and local deployment using llama.cpp or Ollama, thanks to its bf16 precision and AMP training. While the base model is not fine-tuned for downstream tasks, it is designed to be easily adapted through supervised fine-tuning (SFT) or reinforcement learning (RL). Benchmarks on RepoBench, SAFIM, and HumanEval demonstrate its competitive performance, with specialized fine-tuned versions for Python already showing strong improvements.
    Downloads: 0 This Week
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