Model Intelligence Sheet
mradermacher/yue-s1-7b-anneal-jp-kr-cot-gguf overview
About static quants of https://huggingface.co/m-a-p/YuE-s1-7B-anneal-jp-kr-cot weighted/imatrix quants are available at https://huggingface.co/mradermacher/YuE-s1-7B-anneal-jp-kr-cot-i1-GGUF
Downloads
99
Likes
1
Pipeline
—
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
12 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| YuE-s1-7B-anneal-jp-kr-cot.IQ4_XS.gguf | GGUF | IQ4_XS | 3.21 GB | Download |
| YuE-s1-7B-anneal-jp-kr-cot.Q2_K.gguf | GGUF | Q2_K | 2.26 GB | Download |
| YuE-s1-7B-anneal-jp-kr-cot.Q3_K_L.gguf | GGUF | Q3_K_L | 3.11 GB | Download |
| YuE-s1-7B-anneal-jp-kr-cot.Q3_K_M.gguf | GGUF | Q3_K_M | 2.88 GB | Download |
| YuE-s1-7B-anneal-jp-kr-cot.Q3_K_S.gguf | GGUF | Q3_K_S | 2.62 GB | Download |
| YuE-s1-7B-anneal-jp-kr-cot.Q4_K_M.gguf | GGUF | Q4_K_M | 3.53 GB | Download |
| YuE-s1-7B-anneal-jp-kr-cot.Q4_K_S.gguf | GGUF | Q4_K_S | 3.37 GB | Download |
| YuE-s1-7B-anneal-jp-kr-cot.Q5_K_M.gguf | GGUF | Q5_K_M | 4.12 GB | Download |
| YuE-s1-7B-anneal-jp-kr-cot.Q5_K_S.gguf | GGUF | Q5_K_S | 4.03 GB | Download |
| YuE-s1-7B-anneal-jp-kr-cot.Q6_K.gguf | GGUF | Q6_K | 4.76 GB | Download |
| YuE-s1-7B-anneal-jp-kr-cot.Q8_0.gguf | GGUF | — | 6.16 GB | Download |
| YuE-s1-7B-anneal-jp-kr-cot.f16.gguf | GGUF | F16 | 11.60 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "m-a-p/YuE-s1-7B-anneal-jp-kr-cot",
"language": [
"en",
"ja",
"ko"
],
"library_name": "transformers",
"license": "apache-2.0",
"quantized_by": "mradermacher",
"tags": [
"music",
"art",
"text-generation-inference"
],
"frontmatter": {
"base_model": "m-a-p/YuE-s1-7B-anneal-jp-kr-cot",
"language": [
"en",
"ja",
"ko"
],
"library_name": "transformers",
"license": "apache-2.0",
"quantized_by": "mradermacher",
"tags": [
"music",
"art",
"text-generation-inference"
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},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/m-a-p/YuE-s1-7B-anneal-jp-kr-cot weighted/imatrix quants are available at https://huggingface.co/mradermacher/YuE-s1-7B-anneal-jp-kr-cot-i1-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: m-a-p/YuE-s1-7B-anneal-jp-kr-cot\nlanguage:\n- en\n- ja\n- ko\nlibrary_name: transformers\nlicense: apache-2.0\nquantized_by: mradermacher\ntags:\n- music\n- art\n- text-generation-inference\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/m-a-p/YuE-s1-7B-anneal-jp-kr-cot\n\n<!-- provided-files -->\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/YuE-s1-7B-anneal-jp-kr-cot-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/YuE-s1-7B-anneal-jp-kr-cot-GGUF/resolve/main/YuE-s1-7B-anneal-jp-kr-cot.Q2_K.gguf) | Q2_K | 2.5 | |\n| [GGUF](https://huggingface.co/mradermacher/YuE-s1-7B-anneal-jp-kr-cot-GGUF/resolve/main/YuE-s1-7B-anneal-jp-kr-cot.Q3_K_S.gguf) | Q3_K_S | 2.9 | |\n| [GGUF](https://huggingface.co/mradermacher/YuE-s1-7B-anneal-jp-kr-cot-GGUF/resolve/main/YuE-s1-7B-anneal-jp-kr-cot.Q3_K_M.gguf) | Q3_K_M | 3.2 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/YuE-s1-7B-anneal-jp-kr-cot-GGUF/resolve/main/YuE-s1-7B-anneal-jp-kr-cot.Q3_K_L.gguf) | Q3_K_L | 3.4 | |\n| [GGUF](https://huggingface.co/mradermacher/YuE-s1-7B-anneal-jp-kr-cot-GGUF/resolve/main/YuE-s1-7B-anneal-jp-kr-cot.IQ4_XS.gguf) | IQ4_XS | 3.5 | |\n| [GGUF](https://huggingface.co/mradermacher/YuE-s1-7B-anneal-jp-kr-cot-GGUF/resolve/main/YuE-s1-7B-anneal-jp-kr-cot.Q4_K_S.gguf) | Q4_K_S | 3.7 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/YuE-s1-7B-anneal-jp-kr-cot-GGUF/resolve/main/YuE-s1-7B-anneal-jp-kr-cot.Q4_K_M.gguf) | Q4_K_M | 3.9 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/YuE-s1-7B-anneal-jp-kr-cot-GGUF/resolve/main/YuE-s1-7B-anneal-jp-kr-cot.Q5_K_S.gguf) | Q5_K_S | 4.4 | |\n| [GGUF](https://huggingface.co/mradermacher/YuE-s1-7B-anneal-jp-kr-cot-GGUF/resolve/main/YuE-s1-7B-anneal-jp-kr-cot.Q5_K_M.gguf) | Q5_K_M | 4.5 | |\n| [GGUF](https://huggingface.co/mradermacher/YuE-s1-7B-anneal-jp-kr-cot-GGUF/resolve/main/YuE-s1-7B-anneal-jp-kr-cot.Q6_K.gguf) | Q6_K | 5.2 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/YuE-s1-7B-anneal-jp-kr-cot-GGUF/resolve/main/YuE-s1-7B-anneal-jp-kr-cot.Q8_0.gguf) | Q8_0 | 6.7 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/YuE-s1-7B-anneal-jp-kr-cot-GGUF/resolve/main/YuE-s1-7B-anneal-jp-kr-cot.f16.gguf) | f16 | 12.6 | 16 bpw, overkill |\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.\n\n<!-- end -->\n",
"related_quantizations": []
},
"tags": [
"transformers",
"gguf",
"music",
"art",
"text-generation-inference",
"en",
"ja",
"ko",
"base_model:m-a-p/YuE-s1-7B-anneal-jp-kr-cot",
"base_model:quantized:m-a-p/YuE-s1-7B-anneal-jp-kr-cot",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
],
"likes": 1,
"downloads": 99,
"gated": false,
"private": false,
"last_modified": "2025-03-19T03:11:20.000Z",
"created_at": "2025-02-18T10:32:31.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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"sha": "53934108c021583a466e5cd2d45da08bbbf713d9",
"createdAt": "2025-02-18T10:32:31.000Z",
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