Model Intelligence Sheet
mradermacher/pythia-70m-wikipedia-paragraphs-gguf overview
About static quants of https://huggingface.co/agentlans/pythia-70m-wikipedia-paragraphs For a convenient overview and download list, visit our model page for this model. weighted/imatrix quants are available at https://huggingface.co/mradermacher/pythia-70m-wikipedia-paragraphs-i1-GGUF
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Pipeline
text-generation
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
12 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| pythia-70m-wikipedia-paragraphs.IQ4_XS.gguf | GGUF | IQ4_XS | 44.61 MB | Download |
| pythia-70m-wikipedia-paragraphs.Q2_K.gguf | GGUF | Q2_K | 36.72 MB | Download |
| pythia-70m-wikipedia-paragraphs.Q3_K_L.gguf | GGUF | Q3_K_L | 42.82 MB | Download |
| pythia-70m-wikipedia-paragraphs.Q3_K_M.gguf | GGUF | Q3_K_M | 41.88 MB | Download |
| pythia-70m-wikipedia-paragraphs.Q3_K_S.gguf | GGUF | Q3_K_S | 40.29 MB | Download |
| pythia-70m-wikipedia-paragraphs.Q4_K_M.gguf | GGUF | Q4_K_M | 47.02 MB | Download |
| pythia-70m-wikipedia-paragraphs.Q4_K_S.gguf | GGUF | Q4_K_S | 45.94 MB | Download |
| pythia-70m-wikipedia-paragraphs.Q5_K_M.gguf | GGUF | Q5_K_M | 52.12 MB | Download |
| pythia-70m-wikipedia-paragraphs.Q5_K_S.gguf | GGUF | Q5_K_S | 51.26 MB | Download |
| pythia-70m-wikipedia-paragraphs.Q6_K.gguf | GGUF | Q6_K | 56.91 MB | Download |
| pythia-70m-wikipedia-paragraphs.Q8_0.gguf | GGUF | — | 73.17 MB | Download |
| pythia-70m-wikipedia-paragraphs.f16.gguf | GGUF | F16 | 136.10 MB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "agentlans/pythia-70m-wikipedia-paragraphs",
"datasets": [
"agentlans/wikipedia-paragraphs"
],
"language": "en",
"library_name": "transformers",
"license": "apache-2.0",
"mradermacher": {
"readme_rev": 1
},
"quantized_by": "mradermacher",
"tags": [
"text-generation",
"wikipedia",
"pythia"
],
"frontmatter": {
"base_model": "agentlans/pythia-70m-wikipedia-paragraphs",
"datasets": [
"agentlans/wikipedia-paragraphs"
],
"language": "en",
"library_name": "transformers",
"license": "apache-2.0",
"mradermacher": [],
"quantized_by": "mradermacher",
"tags": [
"text-generation",
"wikipedia",
"pythia"
]
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/agentlans/pythia-70m-wikipedia-paragraphs ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/pythia-70m-wikipedia-paragraphs-i1-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: agentlans/pythia-70m-wikipedia-paragraphs\ndatasets:\n- agentlans/wikipedia-paragraphs\nlanguage: en\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n readme_rev: 1\nquantized_by: mradermacher\ntags:\n- text-generation\n- wikipedia\n- pythia\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/agentlans/pythia-70m-wikipedia-paragraphs\n\n<!-- provided-files -->\n\n***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#pythia-70m-wikipedia-paragraphs-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/pythia-70m-wikipedia-paragraphs-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/pythia-70m-wikipedia-paragraphs-GGUF/resolve/main/pythia-70m-wikipedia-paragraphs.Q2_K.gguf) | Q2_K | 0.1 | |\n| [GGUF](https://huggingface.co/mradermacher/pythia-70m-wikipedia-paragraphs-GGUF/resolve/main/pythia-70m-wikipedia-paragraphs.Q3_K_S.gguf) | Q3_K_S | 0.1 | |\n| [GGUF](https://huggingface.co/mradermacher/pythia-70m-wikipedia-paragraphs-GGUF/resolve/main/pythia-70m-wikipedia-paragraphs.Q3_K_M.gguf) | Q3_K_M | 0.1 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/pythia-70m-wikipedia-paragraphs-GGUF/resolve/main/pythia-70m-wikipedia-paragraphs.Q3_K_L.gguf) | Q3_K_L | 0.1 | |\n| [GGUF](https://huggingface.co/mradermacher/pythia-70m-wikipedia-paragraphs-GGUF/resolve/main/pythia-70m-wikipedia-paragraphs.IQ4_XS.gguf) | IQ4_XS | 0.1 | |\n| [GGUF](https://huggingface.co/mradermacher/pythia-70m-wikipedia-paragraphs-GGUF/resolve/main/pythia-70m-wikipedia-paragraphs.Q4_K_S.gguf) | Q4_K_S | 0.1 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/pythia-70m-wikipedia-paragraphs-GGUF/resolve/main/pythia-70m-wikipedia-paragraphs.Q4_K_M.gguf) | Q4_K_M | 0.1 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/pythia-70m-wikipedia-paragraphs-GGUF/resolve/main/pythia-70m-wikipedia-paragraphs.Q5_K_S.gguf) | Q5_K_S | 0.2 | |\n| [GGUF](https://huggingface.co/mradermacher/pythia-70m-wikipedia-paragraphs-GGUF/resolve/main/pythia-70m-wikipedia-paragraphs.Q5_K_M.gguf) | Q5_K_M | 0.2 | |\n| [GGUF](https://huggingface.co/mradermacher/pythia-70m-wikipedia-paragraphs-GGUF/resolve/main/pythia-70m-wikipedia-paragraphs.Q6_K.gguf) | Q6_K | 0.2 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/pythia-70m-wikipedia-paragraphs-GGUF/resolve/main/pythia-70m-wikipedia-paragraphs.Q8_0.gguf) | Q8_0 | 0.2 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/pythia-70m-wikipedia-paragraphs-GGUF/resolve/main/pythia-70m-wikipedia-paragraphs.f16.gguf) | f16 | 0.2 | 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",
"text-generation",
"wikipedia",
"pythia",
"en",
"dataset:agentlans/wikipedia-paragraphs",
"base_model:agentlans/pythia-70m-wikipedia-paragraphs",
"base_model:quantized:agentlans/pythia-70m-wikipedia-paragraphs",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
],
"likes": 0,
"downloads": 93,
"gated": false,
"private": false,
"last_modified": "2025-07-11T03:57:01.000Z",
"created_at": "2025-05-02T19:10:34.000Z",
"pipeline_tag": "text-generation",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
"_id": "681518aac86ba48d4477960e",
"id": "mradermacher/pythia-70m-wikipedia-paragraphs-GGUF",
"modelId": "mradermacher/pythia-70m-wikipedia-paragraphs-GGUF",
"sha": "a2679a68457150a150aaae3d2369aa0fd717f8e1",
"createdAt": "2025-05-02T19:10:34.000Z",
"lastModified": "2025-07-11T03:57:01.000Z",
"author": "mradermacher",
"downloads": 93,
"likes": 0,
"gated": false,
"private": false,
"pipeline_tag": "text-generation",
"library_name": "transformers",
"siblings_count": 14
}