mradermacher/dhanishtha-2.0-preview-i1-gguf overview

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    "base_model": "HelpingAI/Dhanishtha-2.0-preview",
    "datasets": [
      "Abhaykoul/Dhanishtha-R1",
      "open-thoughts/OpenThoughts-114k",
      "Abhaykoul/Dhanishtha-2.0-SUPERTHINKER",
      "Abhaykoul/Dhanishtha-2.0"
    ],
    "language": [
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      "hi",
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      "fr",
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    "library_name": "transformers",
    "license": "apache-2.0",
    "mradermacher": {
      "readme_rev": 1
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    "quantized_by": "mradermacher",
    "tags": [
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      "intermediate-thinking",
      "transformers",
      "conversational",
      "bilingual"
    ],
    "frontmatter": {
      "base_model": "HelpingAI/Dhanishtha-2.0-preview",
      "datasets": [
        "Abhaykoul/Dhanishtha-R1",
        "open-thoughts/OpenThoughts-114k",
        "Abhaykoul/Dhanishtha-2.0-SUPERTHINKER",
        "Abhaykoul/Dhanishtha-2.0"
      ],
      "language": [
        "en",
        "hi",
        "zh",
        "es",
        "fr",
        "de",
        "ja",
        "ko",
        "ar",
        "pt",
        "ru",
        "it",
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      "license": "apache-2.0",
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      "quantized_by": "mradermacher",
      "tags": [
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        "intermediate-thinking",
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        "conversational",
        "bilingual"
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    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         weighted/imatrix quants of https://huggingface.co/HelpingAI/Dhanishtha-2.0-preview  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-GGUF",
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    "readme_markdown": "---\nbase_model: HelpingAI/Dhanishtha-2.0-preview\ndatasets:\n- Abhaykoul/Dhanishtha-R1\n- open-thoughts/OpenThoughts-114k\n- Abhaykoul/Dhanishtha-2.0-SUPERTHINKER\n- Abhaykoul/Dhanishtha-2.0\nlanguage:\n- en\n- hi\n- zh\n- es\n- fr\n- de\n- ja\n- ko\n- ar\n- pt\n- ru\n- it\n- nl\n- tr\n- pl\n- sv\n- da\n- no\n- fi\n- he\n- th\n- vi\n- id\n- ms\n- tl\n- sw\n- yo\n- zu\n- am\n- bn\n- gu\n- kn\n- ml\n- mr\n- ne\n- or\n- pa\n- ta\n- te\n- ur\n- multilingual\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- reasoning\n- intermediate-thinking\n- transformers\n- conversational\n- bilingual\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags: nicoboss -->\n<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->\n<!-- ### quants_skip:  -->\n<!-- ### skip_mmproj:  -->\nweighted/imatrix quants of https://huggingface.co/HelpingAI/Dhanishtha-2.0-preview\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#Dhanishtha-2.0-preview-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-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/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-IQ1_S.gguf) | i1-IQ1_S | 3.7 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-IQ1_M.gguf) | i1-IQ1_M | 3.9 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 4.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-IQ2_XS.gguf) | i1-IQ2_XS | 4.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-IQ2_S.gguf) | i1-IQ2_S | 5.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-IQ2_M.gguf) | i1-IQ2_M | 5.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-Q2_K_S.gguf) | i1-Q2_K_S | 5.5 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-Q2_K.gguf) | i1-Q2_K | 5.9 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 6.0 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-IQ3_XS.gguf) | i1-IQ3_XS | 6.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-Q3_K_S.gguf) | i1-Q3_K_S | 6.8 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-IQ3_S.gguf) | i1-IQ3_S | 6.8 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-IQ3_M.gguf) | i1-IQ3_M | 7.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-Q3_K_M.gguf) | i1-Q3_K_M | 7.4 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-Q3_K_L.gguf) | i1-Q3_K_L | 8.0 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-IQ4_XS.gguf) | i1-IQ4_XS | 8.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-IQ4_NL.gguf) | i1-IQ4_NL | 8.6 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-Q4_0.gguf) | i1-Q4_0 | 8.6 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-Q4_K_S.gguf) | i1-Q4_K_S | 8.7 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-Q4_K_M.gguf) | i1-Q4_K_M | 9.1 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-Q4_1.gguf) | i1-Q4_1 | 9.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-Q5_K_S.gguf) | i1-Q5_K_S | 10.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-Q5_K_M.gguf) | i1-Q5_K_M | 10.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Dhanishtha-2.0-preview-i1-GGUF/resolve/main/Dhanishtha-2.0-preview.i1-Q6_K.gguf) | i1-Q6_K | 12.2 | practically like static Q6_K |\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. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.\n\n<!-- end -->\n",
    "related_quantizations": []
  },
  "tags": [
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    "gguf",
    "reasoning",
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    "en",
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    "multilingual",
    "dataset:Abhaykoul/Dhanishtha-R1",
    "dataset:open-thoughts/OpenThoughts-114k",
    "dataset:Abhaykoul/Dhanishtha-2.0-SUPERTHINKER",
    "dataset:Abhaykoul/Dhanishtha-2.0",
    "base_model:HelpingAI/Dhanishtha-2.0-preview",
    "base_model:quantized:HelpingAI/Dhanishtha-2.0-preview",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "imatrix"
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