taoufik/qwen2.5-vl-3b-instruct-q4_k_m-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "Qwen/Qwen2.5-VL-3B-Instruct",
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license_name": "qwen-research",
    "license_link": "https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct/blob/main/LICENSE",
    "pipeline_tag": "image-text-to-text",
    "tags": [
      "multimodal",
      "llama-cpp",
      "gguf-my-repo"
    ],
    "frontmatter": {
      "base_model": "Qwen/Qwen2.5-VL-3B-Instruct",
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license_name": "qwen-research",
      "license_link": "https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct/blob/main/LICENSE",
      "pipeline_tag": "image-text-to-text",
      "tags": [
        "multimodal",
        "llama-cpp",
        "gguf-my-repo"
      ]
    },
    "hero_image_url": "",
    "summary": "This model was converted to GGUF format from Qwen/Qwen2.5-VL-3B-Instruct using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: Qwen/Qwen2.5-VL-3B-Instruct\nlanguage:\n- en\nlibrary_name: transformers\nlicense_name: qwen-research\nlicense_link: https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct/blob/main/LICENSE\npipeline_tag: image-text-to-text\ntags:\n- multimodal\n- llama-cpp\n- gguf-my-repo\n---\n\n# Taoufik/Qwen2.5-VL-3B-Instruct-Q4_K_M-GGUF\nThis model was converted to GGUF format from [`Qwen/Qwen2.5-VL-3B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.\nRefer to the [original model card](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct) for more details on the model.\n\n## Use with llama.cpp\nInstall llama.cpp through brew (works on Mac and Linux)\n\n```bash\nbrew install llama.cpp\n\n```\nInvoke the llama.cpp server or the CLI.\n\n### CLI:\n```bash\nllama-cli --hf-repo Taoufik/Qwen2.5-VL-3B-Instruct-Q4_K_M-GGUF --hf-file qwen2.5-vl-3b-instruct-q4_k_m.gguf -p \"The meaning to life and the universe is\"\n```\n\n### Server:\n```bash\nllama-server --hf-repo Taoufik/Qwen2.5-VL-3B-Instruct-Q4_K_M-GGUF --hf-file qwen2.5-vl-3b-instruct-q4_k_m.gguf -c 2048\n```\n\nNote: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.\n\nStep 1: Clone llama.cpp from GitHub.\n```\ngit clone https://github.com/ggerganov/llama.cpp\n```\n\nStep 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).\n```\ncd llama.cpp && LLAMA_CURL=1 make\n```\n\nStep 3: Run inference through the main binary.\n```\n./llama-cli --hf-repo Taoufik/Qwen2.5-VL-3B-Instruct-Q4_K_M-GGUF --hf-file qwen2.5-vl-3b-instruct-q4_k_m.gguf -p \"The meaning to life and the universe is\"\n```\nor \n```\n./llama-server --hf-repo Taoufik/Qwen2.5-VL-3B-Instruct-Q4_K_M-GGUF --hf-file qwen2.5-vl-3b-instruct-q4_k_m.gguf -c 2048\n```\n",
    "related_quantizations": []
  },
  "tags": [
    "transformers",
    "gguf",
    "multimodal",
    "llama-cpp",
    "gguf-my-repo",
    "image-text-to-text",
    "en",
    "base_model:Qwen/Qwen2.5-VL-3B-Instruct",
    "base_model:quantized:Qwen/Qwen2.5-VL-3B-Instruct",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 1,
  "downloads": 315,
  "gated": false,
  "private": false,
  "last_modified": "2025-04-05T11:24:14.000Z",
  "created_at": "2025-04-05T11:24:03.000Z",
  "pipeline_tag": "image-text-to-text",
  "library_name": "transformers"
}

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  "id": "Taoufik/Qwen2.5-VL-3B-Instruct-Q4_K_M-GGUF",
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  "sha": "077bef3f647a024f5e2bba3334b0c7b7c31232a3",
  "createdAt": "2025-04-05T11:24:03.000Z",
  "lastModified": "2025-04-05T11:24:14.000Z",
  "author": "Taoufik",
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  "gated": false,
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  "pipeline_tag": "image-text-to-text",
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