mradermacher/smolvlm2-500m-video-instruct-action-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "configint/SmolVLM2-500M-Video-Instruct-Action",
    "datasets": [
      "HuggingFaceM4/the_cauldron",
      "HuggingFaceM4/Docmatix",
      "lmms-lab/LLaVA-OneVision-Data",
      "lmms-lab/M4-Instruct-Data",
      "HuggingFaceFV/finevideo",
      "MAmmoTH-VL/MAmmoTH-VL-Instruct-12M",
      "lmms-lab/LLaVA-Video-178K",
      "orrzohar/Video-STaR",
      "Mutonix/Vript",
      "TIGER-Lab/VISTA-400K",
      "Enxin/MovieChat-1K_train",
      "ShareGPT4Video/ShareGPT4Video"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "frontmatter": {
      "base_model": "configint/SmolVLM2-500M-Video-Instruct-Action",
      "datasets": [
        "HuggingFaceM4/the_cauldron",
        "HuggingFaceM4/Docmatix",
        "lmms-lab/LLaVA-OneVision-Data",
        "lmms-lab/M4-Instruct-Data",
        "HuggingFaceFV/finevideo",
        "MAmmoTH-VL/MAmmoTH-VL-Instruct-12M",
        "lmms-lab/LLaVA-Video-178K",
        "orrzohar/Video-STaR",
        "Mutonix/Vript",
        "TIGER-Lab/VISTA-400K",
        "Enxin/MovieChat-1K_train",
        "ShareGPT4Video/ShareGPT4Video"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "mradermacher": [],
      "quantized_by": "mradermacher"
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      static quants of https://huggingface.co/configint/SmolVLM2-500M-Video-Instruct-Action  ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: configint/SmolVLM2-500M-Video-Instruct-Action\ndatasets:\n- HuggingFaceM4/the_cauldron\n- HuggingFaceM4/Docmatix\n- lmms-lab/LLaVA-OneVision-Data\n- lmms-lab/M4-Instruct-Data\n- HuggingFaceFV/finevideo\n- MAmmoTH-VL/MAmmoTH-VL-Instruct-12M\n- lmms-lab/LLaVA-Video-178K\n- orrzohar/Video-STaR\n- Mutonix/Vript\n- TIGER-Lab/VISTA-400K\n- Enxin/MovieChat-1K_train\n- ShareGPT4Video/ShareGPT4Video\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags:  -->\nstatic quants of https://huggingface.co/configint/SmolVLM2-500M-Video-Instruct-Action\n\n<!-- provided-files -->\n\n***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#SmolVLM2-500M-Video-Instruct-Action-GGUF).***\n\nweighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.\n## Usage\n\nIf you are unsure how to use GGUF files, refer to one of [TheBloke's\nREADMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for\nmore details, including on how to concatenate multi-part files.\n\n## Provided Quants\n\n(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)\n\n| Link | Type | Size/GB | Notes |\n|:-----|:-----|--------:|:------|\n| [GGUF](https://huggingface.co/mradermacher/SmolVLM2-500M-Video-Instruct-Action-GGUF/resolve/main/SmolVLM2-500M-Video-Instruct-Action.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.2 | multi-modal supplement |\n| [GGUF](https://huggingface.co/mradermacher/SmolVLM2-500M-Video-Instruct-Action-GGUF/resolve/main/SmolVLM2-500M-Video-Instruct-Action.mmproj-f16.gguf) | mmproj-f16 | 0.3 | multi-modal supplement |\n| [GGUF](https://huggingface.co/mradermacher/SmolVLM2-500M-Video-Instruct-Action-GGUF/resolve/main/SmolVLM2-500M-Video-Instruct-Action.Q2_K.gguf) | Q2_K | 0.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/SmolVLM2-500M-Video-Instruct-Action-GGUF/resolve/main/SmolVLM2-500M-Video-Instruct-Action.Q3_K_S.gguf) | Q3_K_S | 0.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/SmolVLM2-500M-Video-Instruct-Action-GGUF/resolve/main/SmolVLM2-500M-Video-Instruct-Action.IQ4_XS.gguf) | IQ4_XS | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/SmolVLM2-500M-Video-Instruct-Action-GGUF/resolve/main/SmolVLM2-500M-Video-Instruct-Action.Q3_K_M.gguf) | Q3_K_M | 0.4 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/SmolVLM2-500M-Video-Instruct-Action-GGUF/resolve/main/SmolVLM2-500M-Video-Instruct-Action.Q3_K_L.gguf) | Q3_K_L | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/SmolVLM2-500M-Video-Instruct-Action-GGUF/resolve/main/SmolVLM2-500M-Video-Instruct-Action.Q4_K_S.gguf) | Q4_K_S | 0.4 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/SmolVLM2-500M-Video-Instruct-Action-GGUF/resolve/main/SmolVLM2-500M-Video-Instruct-Action.Q4_K_M.gguf) | Q4_K_M | 0.4 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/SmolVLM2-500M-Video-Instruct-Action-GGUF/resolve/main/SmolVLM2-500M-Video-Instruct-Action.Q5_K_S.gguf) | Q5_K_S | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/SmolVLM2-500M-Video-Instruct-Action-GGUF/resolve/main/SmolVLM2-500M-Video-Instruct-Action.Q5_K_M.gguf) | Q5_K_M | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/SmolVLM2-500M-Video-Instruct-Action-GGUF/resolve/main/SmolVLM2-500M-Video-Instruct-Action.Q6_K.gguf) | Q6_K | 0.5 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/SmolVLM2-500M-Video-Instruct-Action-GGUF/resolve/main/SmolVLM2-500M-Video-Instruct-Action.Q8_0.gguf) | Q8_0 | 0.5 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/SmolVLM2-500M-Video-Instruct-Action-GGUF/resolve/main/SmolVLM2-500M-Video-Instruct-Action.f16.gguf) | f16 | 0.9 | 16 bpw, overkill |\n\nHere is a handy graph by ikawrakow comparing some lower-quality quant\ntypes (lower is better):\n\n![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)\n\nAnd here are Artefact2's thoughts on the matter:\nhttps://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9\n\n## FAQ / Model Request\n\nSee https://huggingface.co/mradermacher/model_requests for some answers to\nquestions you might have and/or if you want some other model quantized.\n\n## Thanks\n\nI thank my company, [nethype GmbH](https://www.nethype.de/), for letting\nme use its servers and providing upgrades to my workstation to enable\nthis work in my free time.\n\n<!-- end -->\n",
    "related_quantizations": []
  },
  "tags": [
    "transformers",
    "gguf",
    "en",
    "dataset:HuggingFaceM4/the_cauldron",
    "dataset:HuggingFaceM4/Docmatix",
    "dataset:lmms-lab/LLaVA-OneVision-Data",
    "dataset:lmms-lab/M4-Instruct-Data",
    "dataset:HuggingFaceFV/finevideo",
    "dataset:MAmmoTH-VL/MAmmoTH-VL-Instruct-12M",
    "dataset:lmms-lab/LLaVA-Video-178K",
    "dataset:orrzohar/Video-STaR",
    "dataset:Mutonix/Vript",
    "dataset:TIGER-Lab/VISTA-400K",
    "dataset:Enxin/MovieChat-1K_train",
    "dataset:ShareGPT4Video/ShareGPT4Video",
    "base_model:configint/SmolVLM2-500M-Video-Instruct-Action",
    "base_model:quantized:configint/SmolVLM2-500M-Video-Instruct-Action",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 0,
  "downloads": 143,
  "gated": false,
  "private": false,
  "last_modified": "2025-07-31T02:46:32.000Z",
  "created_at": "2025-07-11T13:19:03.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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  "author": "mradermacher",
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