mradermacher/10.7b-loyal-mistral-maid-32k-v0.2-a-i1-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
mradermacher/10.7b-loyal-mistral-maid-32k-v0.2-a-i1-gguf overview
About weighted/imatrix quants of https://huggingface.co/xxx777xxxASD/10.7B-Loyal-Mistral-Maid-32k-v0.2-A static quants are available at https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-GGUF
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139
Likes
1
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Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
24 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ1_M.gguf | GGUF | IQ1_M | 2.39 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ1_S.gguf | GGUF | IQ1_S | 2.19 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ2_M.gguf | GGUF | IQ2_M | 3.42 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ2_S.gguf | GGUF | IQ2_S | 3.16 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ2_XS.gguf | GGUF | IQ2_XS | 3.01 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ2_XXS.gguf | GGUF | IQ2_XXS | 2.72 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ3_M.gguf | GGUF | IQ3_M | 4.51 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ3_S.gguf | GGUF | IQ3_S | 4.37 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ3_XS.gguf | GGUF | IQ3_XS | 4.14 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ3_XXS.gguf | GGUF | IQ3_XXS | 3.88 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ4_XS.gguf | GGUF | IQ4_XS | 5.38 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q2_K.gguf | GGUF | Q2_K | 3.73 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q3_K_L.gguf | GGUF | Q3_K_L | 5.26 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q3_K_M.gguf | GGUF | Q3_K_M | 4.84 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q3_K_S.gguf | GGUF | Q3_K_S | 4.34 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q4_0.gguf | GGUF | — | 5.68 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q4_0_4_4.gguf | GGUF | — | 5.66 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q4_0_4_8.gguf | GGUF | — | 5.66 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q4_0_8_8.gguf | GGUF | — | 5.66 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q4_K_M.gguf | GGUF | Q4_K_M | 6.02 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q4_K_S.gguf | GGUF | Q4_K_S | 5.70 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q5_K_M.gguf | GGUF | Q5_K_M | 7.08 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q5_K_S.gguf | GGUF | Q5_K_S | 6.89 GB | Download |
| 10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q6_K.gguf | GGUF | Q6_K | 8.20 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "xxx777xxxASD/10.7B-Loyal-Mistral-Maid-32k-v0.2-A",
"language": [
"en"
],
"library_name": "transformers",
"license": "apache-2.0",
"quantized_by": "mradermacher",
"tags": [
"merge"
],
"frontmatter": {
"base_model": "xxx777xxxASD/10.7B-Loyal-Mistral-Maid-32k-v0.2-A",
"language": [
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"library_name": "transformers",
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"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About weighted/imatrix quants of https://huggingface.co/xxx777xxxASD/10.7B-Loyal-Mistral-Maid-32k-v0.2-A static quants are available at https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: xxx777xxxASD/10.7B-Loyal-Mistral-Maid-32k-v0.2-A\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nquantized_by: mradermacher\ntags:\n- merge\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/xxx777xxxASD/10.7B-Loyal-Mistral-Maid-32k-v0.2-A\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-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/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ1_S.gguf) | i1-IQ1_S | 2.5 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ1_M.gguf) | i1-IQ1_M | 2.7 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 3.0 | |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ2_XS.gguf) | i1-IQ2_XS | 3.3 | |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ2_S.gguf) | i1-IQ2_S | 3.5 | |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ2_M.gguf) | i1-IQ2_M | 3.8 | |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q2_K.gguf) | i1-Q2_K | 4.1 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 4.3 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ3_XS.gguf) | i1-IQ3_XS | 4.5 | |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q3_K_S.gguf) | i1-Q3_K_S | 4.8 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ3_S.gguf) | i1-IQ3_S | 4.8 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ3_M.gguf) | i1-IQ3_M | 4.9 | |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q3_K_M.gguf) | i1-Q3_K_M | 5.3 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q3_K_L.gguf) | i1-Q3_K_L | 5.8 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-IQ4_XS.gguf) | i1-IQ4_XS | 5.9 | |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q4_0_4_4.gguf) | i1-Q4_0_4_4 | 6.2 | fast on arm, low quality |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q4_0_4_8.gguf) | i1-Q4_0_4_8 | 6.2 | fast on arm+i8mm, low quality |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q4_0_8_8.gguf) | i1-Q4_0_8_8 | 6.2 | fast on arm+sve, low quality |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q4_0.gguf) | i1-Q4_0 | 6.2 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q4_K_S.gguf) | i1-Q4_K_S | 6.2 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q4_K_M.gguf) | i1-Q4_K_M | 6.6 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q5_K_S.gguf) | i1-Q5_K_S | 7.5 | |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q5_K_M.gguf) | i1-Q5_K_M | 7.7 | |\n| [GGUF](https://huggingface.co/mradermacher/10.7B-Loyal-Mistral-Maid-32k-v0.2-A-i1-GGUF/resolve/main/10.7B-Loyal-Mistral-Maid-32k-v0.2-A.i1-Q6_K.gguf) | i1-Q6_K | 8.9 | 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": []
},
"tags": [
"transformers",
"gguf",
"merge",
"en",
"base_model:xxx777xxxASD/10.7B-Loyal-Mistral-Maid-32k-v0.2-A",
"base_model:quantized:xxx777xxxASD/10.7B-Loyal-Mistral-Maid-32k-v0.2-A",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
],
"likes": 1,
"downloads": 139,
"gated": false,
"private": false,
"last_modified": "2024-12-03T11:01:54.000Z",
"created_at": "2024-12-03T07:21:27.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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"sha": "266b0b49515a53e508cff06343e6efaa21f2a721",
"createdAt": "2024-12-03T07:21:27.000Z",
"lastModified": "2024-12-03T11:01:54.000Z",
"author": "mradermacher",
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