Model Intelligence Sheet
mradermacher/kyro-n1.1-3b-pytorch-i1-gguf overview
About weighted/imatrix quants of https://huggingface.co/open-neo/Kyro-n1.1-3B-pytorch static quants are available at https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-GGUF
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Repository Files & Downloads
24 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Kyro-n1.1-3B-pytorch.i1-IQ1_M.gguf | GGUF | IQ1_M | 810.65 MB | Download |
| Kyro-n1.1-3B-pytorch.i1-IQ1_S.gguf | GGUF | IQ1_S | 754.45 MB | Download |
| Kyro-n1.1-3B-pytorch.i1-IQ2_M.gguf | GGUF | IQ2_M | 1.06 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-IQ2_S.gguf | GGUF | IQ2_S | 1012.74 MB | Download |
| Kyro-n1.1-3B-pytorch.i1-IQ2_XS.gguf | GGUF | IQ2_XS | 983.76 MB | Download |
| Kyro-n1.1-3B-pytorch.i1-IQ2_XXS.gguf | GGUF | IQ2_XXS | 904.32 MB | Download |
| Kyro-n1.1-3B-pytorch.i1-IQ3_M.gguf | GGUF | IQ3_M | 1.39 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-IQ3_S.gguf | GGUF | IQ3_S | 1.36 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-IQ3_XS.gguf | GGUF | IQ3_XS | 1.30 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-IQ3_XXS.gguf | GGUF | IQ3_XXS | 1.19 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-IQ4_NL.gguf | GGUF | IQ4_NL | 1.70 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-IQ4_XS.gguf | GGUF | IQ4_XS | 1.62 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-Q2_K.gguf | GGUF | Q2_K | 1.19 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-Q2_K_S.gguf | GGUF | Q2_K_S | 1.12 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-Q3_K_L.gguf | GGUF | Q3_K_L | 1.59 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-Q3_K_M.gguf | GGUF | Q3_K_M | 1.48 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-Q3_K_S.gguf | GGUF | Q3_K_S | 1.35 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-Q4_0.gguf | GGUF | — | 1.70 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-Q4_1.gguf | GGUF | — | 1.86 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-Q4_K_M.gguf | GGUF | Q4_K_M | 1.80 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-Q4_K_S.gguf | GGUF | Q4_K_S | 1.71 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-Q5_K_M.gguf | GGUF | Q5_K_M | 2.07 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-Q5_K_S.gguf | GGUF | Q5_K_S | 2.02 GB | Download |
| Kyro-n1.1-3B-pytorch.i1-Q6_K.gguf | GGUF | Q6_K | 2.36 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
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"base_model": "open-neo/Kyro-n1.1-3B-pytorch",
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"base_model": "open-neo/Kyro-n1.1-3B-pytorch",
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"summary": "## About weighted/imatrix quants of https://huggingface.co/open-neo/Kyro-n1.1-3B-pytorch static quants are available at https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-GGUF",
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"readme_markdown": "---\nbase_model: open-neo/Kyro-n1.1-3B-pytorch\nlanguage:\n- en\n- zh\n- fr\n- es\n- pt\n- de\n- it\n- ru\n- ja\n- ko\n- vi\n- th\n- ar\n- fa\n- he\n- tr\n- cs\n- pl\n- hi\n- bn\n- ur\n- id\n- ms\n- lo\n- my\n- ceb\n- km\n- tl\n- nl\nlibrary_name: transformers\nlicense: other\nlicense_link: https://huggingface.co/Qwen/Qwen2.5-3B-Instruct/blob/main/LICENSE\nlicense_name: qwen-research\nquantized_by: mradermacher\ntags:\n- reasoning\n- kyro\n- open-neo\n- open-source\n- deepseek-r1\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type: -->\n<!-- ### tags: nicoboss -->\nweighted/imatrix quants of https://huggingface.co/open-neo/Kyro-n1.1-3B-pytorch\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-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/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-IQ1_S.gguf) | i1-IQ1_S | 0.9 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-IQ1_M.gguf) | i1-IQ1_M | 1.0 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 1.0 | |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-IQ2_XS.gguf) | i1-IQ2_XS | 1.1 | |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-IQ2_S.gguf) | i1-IQ2_S | 1.2 | |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-IQ2_M.gguf) | i1-IQ2_M | 1.2 | |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-Q2_K_S.gguf) | i1-Q2_K_S | 1.3 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-Q2_K.gguf) | i1-Q2_K | 1.4 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 1.4 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-IQ3_XS.gguf) | i1-IQ3_XS | 1.5 | |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-Q3_K_S.gguf) | i1-Q3_K_S | 1.6 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-IQ3_S.gguf) | i1-IQ3_S | 1.6 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-IQ3_M.gguf) | i1-IQ3_M | 1.6 | |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-Q3_K_M.gguf) | i1-Q3_K_M | 1.7 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-Q3_K_L.gguf) | i1-Q3_K_L | 1.8 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-IQ4_XS.gguf) | i1-IQ4_XS | 1.8 | |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-IQ4_NL.gguf) | i1-IQ4_NL | 1.9 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-Q4_0.gguf) | i1-Q4_0 | 1.9 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-Q4_K_S.gguf) | i1-Q4_K_S | 1.9 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-Q4_K_M.gguf) | i1-Q4_K_M | 2.0 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-Q4_1.gguf) | i1-Q4_1 | 2.1 | |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-Q5_K_S.gguf) | i1-Q5_K_S | 2.3 | |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-Q5_K_M.gguf) | i1-Q5_K_M | 2.3 | |\n| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-3B-pytorch-i1-GGUF/resolve/main/Kyro-n1.1-3B-pytorch.i1-Q6_K.gguf) | i1-Q6_K | 2.6 | practically like static Q6_K |\n\nHere is a handy graph by ikawrakow comparing some lower-quality quant\ntypes (lower is better):\n\n\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": []
},
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Source payload excerpt (from Hugging Face API)
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