mmnga/axcxept-phi-4-open-r1-distill-ezov1-gguf Q5_K_M GGUF - Free GGUF Download is indexed on GraySoft with repository links, GGUF quant files, and Hugging Face metadata. This page helps you pick a local model for guIDE or other runtimes. See related models in the same shard below.
Model Intelligence Sheet
mmnga/axcxept-phi-4-open-r1-distill-ezov1-gguf overview
AXCXEPTさんが公開しているphi-4-open-R1-Distill-EZOv1のggufフォーマット変換版です。 imatrixのデータはTFMC/imatrix-dataset-for-japanese-llmを使用して作成しました。
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1,466
Likes
3
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Visibility
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Repository Files & Downloads
24 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-IQ1_M.gguf | GGUF | IQ1_M | 3.35 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-IQ1_S.gguf | GGUF | IQ1_S | 3.09 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-IQ2_M.gguf | GGUF | IQ2_M | 4.76 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-IQ2_S.gguf | GGUF | IQ2_S | 4.41 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-IQ2_XS.gguf | GGUF | IQ2_XS | 4.18 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-IQ2_XXS.gguf | GGUF | IQ2_XXS | 3.79 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-IQ3_M.gguf | GGUF | IQ3_M | 6.44 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-IQ3_S.gguf | GGUF | IQ3_S | 6.06 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-IQ3_XS.gguf | GGUF | IQ3_XS | 5.82 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-IQ3_XXS.gguf | GGUF | IQ3_XXS | 5.45 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-IQ4_NL.gguf | GGUF | IQ4_NL | 7.81 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-IQ4_XS.gguf | GGUF | IQ4_XS | 7.40 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-Q2_K.gguf | GGUF | Q2_K | 5.17 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-Q3_K_L.gguf | GGUF | Q3_K_L | 7.39 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-Q3_K_M.gguf | GGUF | Q3_K_M | 6.86 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-Q3_K_S.gguf | GGUF | Q3_K_S | 6.06 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-Q4_0.gguf | GGUF | — | 7.81 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-Q4_K_M.gguf | GGUF | Q4_K_M | 8.43 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-Q4_K_S.gguf | GGUF | Q4_K_S | 7.86 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-Q5_0.gguf | GGUF | — | 9.45 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-Q5_K_M.gguf | GGUF | Q5_K_M | 9.88 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-Q5_K_S.gguf | GGUF | Q5_K_S | 9.45 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-Q6_K.gguf | GGUF | Q6_K | 11.20 GB | Download |
| AXCXEPT-phi-4-open-R1-Distill-EZOv1-Q8_0.gguf | GGUF | — | 14.51 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"license": "mit",
"language": [
"en",
"ja"
],
"datasets": [
"TFMC/imatrix-dataset-for-japanese-llm"
],
"base_model": [
"AXCXEPT/AXCXEPT-phi-4-open-R1-Distill-EZOv1"
],
"frontmatter": {},
"hero_image_url": "",
"summary": "AXCXEPTさんが公開しているphi-4-open-R1-Distill-EZOv1のggufフォーマット変換版です。 imatrixのデータはTFMC/imatrix-dataset-for-japanese-llmを使用して作成しました。",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "\n---\nlicense: mit\nlanguage:\n- en\n- ja\ndatasets:\n- TFMC/imatrix-dataset-for-japanese-llm\nbase_model:\n- AXCXEPT/AXCXEPT-phi-4-open-R1-Distill-EZOv1\n---\n\n# AXCXEPT-phi-4-open-R1-Distill-EZOv1-gguf\n[AXCXEPTさんが公開しているphi-4-open-R1-Distill-EZOv1](https://huggingface.co/AXCXEPT/phi-4-open-R1-Distill-EZOv1)のggufフォーマット変換版です。 \n\nimatrixのデータは[TFMC/imatrix-dataset-for-japanese-llm](https://huggingface.co/datasets/TFMC/imatrix-dataset-for-japanese-llm)を使用して作成しました。 \n \n## Usage\n\n```\ngit clone https://github.com/ggerganov/llama.cpp.git\ncd llama.cpp\ncmake -B build -DGGML_CUDA=ON\ncmake --build build --config Release\nbuild/bin/llama-cli -m 'AXCXEPT-phi-4-open-R1-Distill-EZOv1-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv\n```\n",
"related_quantizations": []
},
"tags": [
"gguf",
"en",
"ja",
"dataset:TFMC/imatrix-dataset-for-japanese-llm",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
],
"likes": 3,
"downloads": 1466,
"gated": false,
"private": false,
"last_modified": "2025-01-27T16:04:19.000Z",
"created_at": "2025-01-27T12:31:36.000Z",
"pipeline_tag": "",
"library_name": ""
}
Source payload excerpt (from Hugging Face API)
{
"_id": "67977ca84a10be71099f5c93",
"id": "mmnga/AXCXEPT-phi-4-open-R1-Distill-EZOv1-gguf",
"modelId": "mmnga/AXCXEPT-phi-4-open-R1-Distill-EZOv1-gguf",
"sha": "4fca9ed33e6e55b224484a78d966595cefbb9e77",
"createdAt": "2025-01-27T12:31:36.000Z",
"lastModified": "2025-01-27T16:04:19.000Z",
"author": "mmnga",
"downloads": 1466,
"likes": 3,
"gated": false,
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"pipeline_tag": "",
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"siblings_count": 26
}