Showing 7 open source projects for "ollama"

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  • 1
    Qwen3

    Qwen3

    Qwen3 is the large language model series developed by Qwen team

    Qwen3 is a cutting-edge large language model (LLM) series developed by the Qwen team at Alibaba Cloud. The latest updated version, Qwen3-235B-A22B-Instruct-2507, features significant improvements in instruction-following, reasoning, knowledge coverage, and long-context understanding up to 256K tokens. It delivers higher quality and more helpful text generation across multiple languages and domains, including mathematics, coding, science, and tool usage. Various quantized versions,...
    Downloads: 23 This Week
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  • 2
    GLM-OCR

    GLM-OCR

    Accurate × Fast × Comprehensive

    GLM-OCR is an open-source multimodal optical character recognition (OCR) model built on a GLM-V encoder–decoder foundation that brings robust, accurate document understanding to complex real-world layouts and modalities. Designed to handle text recognition, table parsing, formula extraction, and general information retrieval from documents containing mixed content, GLM-OCR excels across major benchmarks while remaining highly efficient with a relatively compact parameter size (~0.9B),...
    Downloads: 7 This Week
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  • 3
    OpenAI Harmony

    OpenAI Harmony

    Renderer for the harmony response format to be used with gpt-oss

    ...The format is essential for ensuring gpt-oss models operate correctly, as they are trained to rely on this structure for generating and organizing their responses. For users accessing gpt-oss through third-party providers like HuggingFace, Ollama, or vLLM, Harmony formatting is handled automatically, but developers building custom inference setups must implement it directly. With its flexible design, Harmony serves as the foundation for creating more interpretable, controlled, and extensible interactions with open-weight language models.
    Downloads: 9 This Week
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  • 4
    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: 34 This Week
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  • 5
    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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  • 6
    gpt-oss-120b

    gpt-oss-120b

    OpenAI’s open-weight 120B model optimized for reasoning and tooling

    ...The model supports fine-tuning, chain-of-thought reasoning, and structured outputs, making it ideal for complex workflows. It operates in OpenAI’s Harmony response format and can be deployed via Transformers, vLLM, Ollama, LM Studio, and PyTorch. Developers can control the reasoning level (low, medium, high) to balance speed and depth depending on the task. Released under the Apache 2.0 license, it enables both commercial and research applications. The model supports function calling, web browsing, and code execution, streamlining intelligent agent development.
    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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