mradermacher/arco-reflection-gguf Q2_K 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/arco-reflection-gguf overview
About static quants of https://huggingface.co/appvoid/arco-reflection weighted/imatrix quants are available at https://huggingface.co/mradermacher/arco-reflection-i1-GGUF
Downloads
101
Likes
0
Pipeline
—
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
14 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| arco-reflection.IQ3_M.gguf | GGUF | IQ3_M | 238.40 MB | Download |
| arco-reflection.IQ3_S.gguf | GGUF | IQ3_S | 229.64 MB | Download |
| arco-reflection.IQ3_XS.gguf | GGUF | IQ3_XS | 220.36 MB | Download |
| arco-reflection.IQ4_XS.gguf | GGUF | IQ4_XS | 276.49 MB | Download |
| arco-reflection.Q2_K.gguf | GGUF | Q2_K | 199.89 MB | Download |
| arco-reflection.Q3_K_L.gguf | GGUF | Q3_K_L | 268.31 MB | Download |
| arco-reflection.Q3_K_M.gguf | GGUF | Q3_K_M | 250.59 MB | Download |
| arco-reflection.Q3_K_S.gguf | GGUF | Q3_K_S | 229.64 MB | Download |
| arco-reflection.Q4_K_M.gguf | GGUF | Q4_K_M | 303.15 MB | Download |
| arco-reflection.Q4_K_S.gguf | GGUF | Q4_K_S | 290.52 MB | Download |
| arco-reflection.Q5_K_M.gguf | GGUF | Q5_K_M | 351.39 MB | Download |
| arco-reflection.Q5_K_S.gguf | GGUF | Q5_K_S | 343.82 MB | Download |
| arco-reflection.Q6_K.gguf | GGUF | Q6_K | 402.64 MB | Download |
| arco-reflection.Q8_0.gguf | GGUF | — | 521.25 MB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "appvoid/arco-reflection",
"language": [
"en"
],
"library_name": "transformers",
"license": "apache-2.0",
"quantized_by": "mradermacher",
"tags": [
"text-generation-inference",
"transformers",
"unsloth",
"llama",
"trl",
"sft"
],
"frontmatter": {
"base_model": "appvoid/arco-reflection",
"language": [
"en"
],
"library_name": "transformers",
"license": "apache-2.0",
"quantized_by": "mradermacher",
"tags": [
"text-generation-inference",
"transformers",
"unsloth",
"llama",
"trl",
"sft"
]
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/appvoid/arco-reflection weighted/imatrix quants are available at https://huggingface.co/mradermacher/arco-reflection-i1-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: appvoid/arco-reflection\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nquantized_by: mradermacher\ntags:\n- text-generation-inference\n- transformers\n- unsloth\n- llama\n- trl\n- sft\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/appvoid/arco-reflection\n\n<!-- provided-files -->\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/arco-reflection-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/arco-reflection-GGUF/resolve/main/arco-reflection.Q2_K.gguf) | Q2_K | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/arco-reflection-GGUF/resolve/main/arco-reflection.IQ3_XS.gguf) | IQ3_XS | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/arco-reflection-GGUF/resolve/main/arco-reflection.IQ3_S.gguf) | IQ3_S | 0.3 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/arco-reflection-GGUF/resolve/main/arco-reflection.Q3_K_S.gguf) | Q3_K_S | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/arco-reflection-GGUF/resolve/main/arco-reflection.IQ3_M.gguf) | IQ3_M | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/arco-reflection-GGUF/resolve/main/arco-reflection.Q3_K_M.gguf) | Q3_K_M | 0.4 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/arco-reflection-GGUF/resolve/main/arco-reflection.Q3_K_L.gguf) | Q3_K_L | 0.4 | |\n| [GGUF](https://huggingface.co/mradermacher/arco-reflection-GGUF/resolve/main/arco-reflection.IQ4_XS.gguf) | IQ4_XS | 0.4 | |\n| [GGUF](https://huggingface.co/mradermacher/arco-reflection-GGUF/resolve/main/arco-reflection.Q4_K_S.gguf) | Q4_K_S | 0.4 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/arco-reflection-GGUF/resolve/main/arco-reflection.Q4_K_M.gguf) | Q4_K_M | 0.4 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/arco-reflection-GGUF/resolve/main/arco-reflection.Q5_K_S.gguf) | Q5_K_S | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/arco-reflection-GGUF/resolve/main/arco-reflection.Q5_K_M.gguf) | Q5_K_M | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/arco-reflection-GGUF/resolve/main/arco-reflection.Q6_K.gguf) | Q6_K | 0.5 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/arco-reflection-GGUF/resolve/main/arco-reflection.Q8_0.gguf) | Q8_0 | 0.6 | fast, best quality |\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",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"sft",
"en",
"base_model:appvoid/arco-reflection",
"base_model:quantized:appvoid/arco-reflection",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
],
"likes": 0,
"downloads": 101,
"gated": false,
"private": false,
"last_modified": "2024-09-08T15:07:21.000Z",
"created_at": "2024-09-08T15:01:29.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
"_id": "66ddbc49becd5c1c0cf51c3a",
"id": "mradermacher/arco-reflection-GGUF",
"modelId": "mradermacher/arco-reflection-GGUF",
"sha": "2e0b02d15b6c8e4b479d1e93928a48d50d640182",
"createdAt": "2024-09-08T15:01:29.000Z",
"lastModified": "2024-09-08T15:07:21.000Z",
"author": "mradermacher",
"downloads": 101,
"likes": 0,
"gated": false,
"private": false,
"pipeline_tag": "",
"library_name": "transformers",
"siblings_count": 16
}