mradermacher/qwen3-nemotron-8b-brrm-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "nvidia/Qwen3-Nemotron-8B-BRRM",
    "datasets": [
      "nvidia/HelpSteer3",
      "Skywork/Skywork-Reward-Preference-80K-v0.2",
      "Vezora/Code-Preference-Pairs",
      "xinlai/Math-Step-DPO-10K"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "other",
    "license_link": "https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-internal-scientific-research-and-development-model-license/",
    "license_name": "nvidia-internal-scientific-research-and-development-model-license",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "reward_model",
      "nvidia",
      "qwen3"
    ],
    "frontmatter": {
      "base_model": "nvidia/Qwen3-Nemotron-8B-BRRM",
      "datasets": [
        "nvidia/HelpSteer3",
        "Skywork/Skywork-Reward-Preference-80K-v0.2",
        "Vezora/Code-Preference-Pairs",
        "xinlai/Math-Step-DPO-10K"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "other",
      "license_link": "https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-internal-scientific-research-and-development-model-license/",
      "license_name": "nvidia-internal-scientific-research-and-development-model-license",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "reward_model",
        "nvidia",
        "qwen3"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         static quants of https://huggingface.co/nvidia/Qwen3-Nemotron-8B-BRRM  ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen3-Nemotron-8B-BRRM-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: nvidia/Qwen3-Nemotron-8B-BRRM\ndatasets:\n- nvidia/HelpSteer3\n- Skywork/Skywork-Reward-Preference-80K-v0.2\n- Vezora/Code-Preference-Pairs\n- xinlai/Math-Step-DPO-10K\nlanguage:\n- en\nlibrary_name: transformers\nlicense: other\nlicense_link: https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-internal-scientific-research-and-development-model-license/\nlicense_name: nvidia-internal-scientific-research-and-development-model-license\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- reward_model\n- nvidia\n- qwen3\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags:  -->\n<!-- ### quants:  x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->\n<!-- ### quants_skip:  -->\n<!-- ### skip_mmproj:  -->\nstatic quants of https://huggingface.co/nvidia/Qwen3-Nemotron-8B-BRRM\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#Qwen3-Nemotron-8B-BRRM-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen3-Nemotron-8B-BRRM-i1-GGUF\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/Qwen3-Nemotron-8B-BRRM-GGUF/resolve/main/Qwen3-Nemotron-8B-BRRM.Q2_K.gguf) | Q2_K | 3.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-Nemotron-8B-BRRM-GGUF/resolve/main/Qwen3-Nemotron-8B-BRRM.Q3_K_S.gguf) | Q3_K_S | 3.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-Nemotron-8B-BRRM-GGUF/resolve/main/Qwen3-Nemotron-8B-BRRM.Q3_K_M.gguf) | Q3_K_M | 4.2 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-Nemotron-8B-BRRM-GGUF/resolve/main/Qwen3-Nemotron-8B-BRRM.Q3_K_L.gguf) | Q3_K_L | 4.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-Nemotron-8B-BRRM-GGUF/resolve/main/Qwen3-Nemotron-8B-BRRM.IQ4_XS.gguf) | IQ4_XS | 4.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-Nemotron-8B-BRRM-GGUF/resolve/main/Qwen3-Nemotron-8B-BRRM.Q4_K_S.gguf) | Q4_K_S | 4.9 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-Nemotron-8B-BRRM-GGUF/resolve/main/Qwen3-Nemotron-8B-BRRM.Q4_K_M.gguf) | Q4_K_M | 5.1 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-Nemotron-8B-BRRM-GGUF/resolve/main/Qwen3-Nemotron-8B-BRRM.Q5_K_S.gguf) | Q5_K_S | 5.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-Nemotron-8B-BRRM-GGUF/resolve/main/Qwen3-Nemotron-8B-BRRM.Q5_K_M.gguf) | Q5_K_M | 6.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-Nemotron-8B-BRRM-GGUF/resolve/main/Qwen3-Nemotron-8B-BRRM.Q6_K.gguf) | Q6_K | 6.8 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-Nemotron-8B-BRRM-GGUF/resolve/main/Qwen3-Nemotron-8B-BRRM.Q8_0.gguf) | Q8_0 | 8.8 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/Qwen3-Nemotron-8B-BRRM-GGUF/resolve/main/Qwen3-Nemotron-8B-BRRM.f16.gguf) | f16 | 16.5 | 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",
    "reward_model",
    "nvidia",
    "qwen3",
    "en",
    "dataset:nvidia/HelpSteer3",
    "dataset:Skywork/Skywork-Reward-Preference-80K-v0.2",
    "dataset:Vezora/Code-Preference-Pairs",
    "dataset:xinlai/Math-Step-DPO-10K",
    "base_model:nvidia/Qwen3-Nemotron-8B-BRRM",
    "base_model:quantized:nvidia/Qwen3-Nemotron-8B-BRRM",
    "license:other",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 0,
  "downloads": 238,
  "gated": false,
  "private": false,
  "last_modified": "2025-10-30T10:06:03.000Z",
  "created_at": "2025-10-30T07:57:07.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

{
  "_id": "69031a53c6ce81ea1c3f3fc5",
  "id": "mradermacher/Qwen3-Nemotron-8B-BRRM-GGUF",
  "modelId": "mradermacher/Qwen3-Nemotron-8B-BRRM-GGUF",
  "sha": "875f01961ad4d948fee46ec350ff875ca6925e4f",
  "createdAt": "2025-10-30T07:57:07.000Z",
  "lastModified": "2025-10-30T10:06:03.000Z",
  "author": "mradermacher",
  "downloads": 238,
  "likes": 0,
  "gated": false,
  "private": false,
  "pipeline_tag": "",
  "library_name": "transformers",
  "siblings_count": 14
}