Model Intelligence Sheet
mradermacher/smolllamix-8x101m-take2-gguf overview
About static quants of https://huggingface.co/chargoddard/SmolLlamix-8x101M-take2 weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Downloads
108
Likes
1
Pipeline
—
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
14 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| SmolLlamix-8x101M-take2.IQ3_M.gguf | GGUF | IQ3_M | 208.15 MB | Download |
| SmolLlamix-8x101M-take2.IQ3_S.gguf | GGUF | IQ3_S | 203.37 MB | Download |
| SmolLlamix-8x101M-take2.IQ3_XS.gguf | GGUF | IQ3_XS | 194.77 MB | Download |
| SmolLlamix-8x101M-take2.IQ4_XS.gguf | GGUF | IQ4_XS | 239.01 MB | Download |
| SmolLlamix-8x101M-take2.Q2_K.gguf | GGUF | Q2_K | 178.70 MB | Download |
| SmolLlamix-8x101M-take2.Q3_K_L.gguf | GGUF | Q3_K_L | 230.34 MB | Download |
| SmolLlamix-8x101M-take2.Q3_K_M.gguf | GGUF | Q3_K_M | 217.71 MB | Download |
| SmolLlamix-8x101M-take2.Q3_K_S.gguf | GGUF | Q3_K_S | 203.37 MB | Download |
| SmolLlamix-8x101M-take2.Q4_K_M.gguf | GGUF | Q4_K_M | 259.25 MB | Download |
| SmolLlamix-8x101M-take2.Q4_K_S.gguf | GGUF | Q4_K_S | 249.97 MB | Download |
| SmolLlamix-8x101M-take2.Q5_K_M.gguf | GGUF | Q5_K_M | 298.62 MB | Download |
| SmolLlamix-8x101M-take2.Q5_K_S.gguf | GGUF | Q5_K_S | 293.83 MB | Download |
| SmolLlamix-8x101M-take2.Q6_K.gguf | GGUF | Q6_K | 340.89 MB | Download |
| SmolLlamix-8x101M-take2.Q8_0.gguf | GGUF | — | 426.69 MB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "chargoddard/SmolLlamix-8x101M-take2",
"datasets": [
"togethercomputer/RedPajama-Data-1T-Sample"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "apache-2.0",
"quantized_by": "mradermacher",
"frontmatter": {
"base_model": "chargoddard/SmolLlamix-8x101M-take2",
"datasets": [
"togethercomputer/RedPajama-Data-1T-Sample"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "apache-2.0",
"quantized_by": "mradermacher"
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/chargoddard/SmolLlamix-8x101M-take2 weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: chargoddard/SmolLlamix-8x101M-take2\ndatasets:\n- togethercomputer/RedPajama-Data-1T-Sample\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nquantized_by: mradermacher\n---\n## About\n\nstatic quants of https://huggingface.co/chargoddard/SmolLlamix-8x101M-take2\n\n<!-- provided-files -->\nweighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.\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/SmolLlamix-8x101M-take2-GGUF/resolve/main/SmolLlamix-8x101M-take2.Q2_K.gguf) | Q2_K | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/SmolLlamix-8x101M-take2-GGUF/resolve/main/SmolLlamix-8x101M-take2.IQ3_XS.gguf) | IQ3_XS | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/SmolLlamix-8x101M-take2-GGUF/resolve/main/SmolLlamix-8x101M-take2.IQ3_S.gguf) | IQ3_S | 0.3 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/SmolLlamix-8x101M-take2-GGUF/resolve/main/SmolLlamix-8x101M-take2.Q3_K_S.gguf) | Q3_K_S | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/SmolLlamix-8x101M-take2-GGUF/resolve/main/SmolLlamix-8x101M-take2.IQ3_M.gguf) | IQ3_M | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/SmolLlamix-8x101M-take2-GGUF/resolve/main/SmolLlamix-8x101M-take2.Q3_K_M.gguf) | Q3_K_M | 0.3 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/SmolLlamix-8x101M-take2-GGUF/resolve/main/SmolLlamix-8x101M-take2.Q3_K_L.gguf) | Q3_K_L | 0.3 | |\n| [GGUF](https://huggingface.co/mradermacher/SmolLlamix-8x101M-take2-GGUF/resolve/main/SmolLlamix-8x101M-take2.IQ4_XS.gguf) | IQ4_XS | 0.4 | |\n| [GGUF](https://huggingface.co/mradermacher/SmolLlamix-8x101M-take2-GGUF/resolve/main/SmolLlamix-8x101M-take2.Q4_K_S.gguf) | Q4_K_S | 0.4 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/SmolLlamix-8x101M-take2-GGUF/resolve/main/SmolLlamix-8x101M-take2.Q4_K_M.gguf) | Q4_K_M | 0.4 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/SmolLlamix-8x101M-take2-GGUF/resolve/main/SmolLlamix-8x101M-take2.Q5_K_S.gguf) | Q5_K_S | 0.4 | |\n| [GGUF](https://huggingface.co/mradermacher/SmolLlamix-8x101M-take2-GGUF/resolve/main/SmolLlamix-8x101M-take2.Q5_K_M.gguf) | Q5_K_M | 0.4 | |\n| [GGUF](https://huggingface.co/mradermacher/SmolLlamix-8x101M-take2-GGUF/resolve/main/SmolLlamix-8x101M-take2.Q6_K.gguf) | Q6_K | 0.5 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/SmolLlamix-8x101M-take2-GGUF/resolve/main/SmolLlamix-8x101M-take2.Q8_0.gguf) | Q8_0 | 0.5 | 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",
"en",
"dataset:togethercomputer/RedPajama-Data-1T-Sample",
"base_model:chargoddard/SmolLlamix-8x101M-take2",
"base_model:quantized:chargoddard/SmolLlamix-8x101M-take2",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
],
"likes": 1,
"downloads": 108,
"gated": false,
"private": false,
"last_modified": "2024-05-06T06:10:59.000Z",
"created_at": "2024-03-17T11:23:54.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
"_id": "65f6d2ca01523ed70327d9f6",
"id": "mradermacher/SmolLlamix-8x101M-take2-GGUF",
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"sha": "8c367431507090dd00850b93089875c921819825",
"createdAt": "2024-03-17T11:23:54.000Z",
"lastModified": "2024-05-06T06:10:59.000Z",
"author": "mradermacher",
"downloads": 108,
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"siblings_count": 16
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