Model Intelligence Sheet
mradermacher/tessa-t1-32b-i1-gguf overview
About weighted/imatrix quants of https://huggingface.co/Tesslate/Tessa-T1-32B For a convenient overview and download list, visit our model page for this model. static quants are available at https://huggingface.co/mradermacher/Tessa-T1-32B-GGUF
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Pipeline
—
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
23 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Tessa-T1-32B.i1-IQ1_M.gguf | GGUF | IQ1_M | 7.39 GB | Download |
| Tessa-T1-32B.i1-IQ1_S.gguf | GGUF | IQ1_S | 6.77 GB | Download |
| Tessa-T1-32B.i1-IQ2_M.gguf | GGUF | IQ2_M | 10.49 GB | Download |
| Tessa-T1-32B.i1-IQ2_S.gguf | GGUF | IQ2_S | 9.67 GB | Download |
| Tessa-T1-32B.i1-IQ2_XS.gguf | GGUF | IQ2_XS | 9.27 GB | Download |
| Tessa-T1-32B.i1-IQ2_XXS.gguf | GGUF | IQ2_XXS | 8.41 GB | Download |
| Tessa-T1-32B.i1-IQ3_M.gguf | GGUF | IQ3_M | 13.79 GB | Download |
| Tessa-T1-32B.i1-IQ3_S.gguf | GGUF | IQ3_S | 13.45 GB | Download |
| Tessa-T1-32B.i1-IQ3_XS.gguf | GGUF | IQ3_XS | 12.76 GB | Download |
| Tessa-T1-32B.i1-IQ3_XXS.gguf | GGUF | IQ3_XXS | 11.96 GB | Download |
| Tessa-T1-32B.i1-IQ4_XS.gguf | GGUF | IQ4_XS | 16.48 GB | Download |
| Tessa-T1-32B.i1-Q2_K.gguf | GGUF | Q2_K | 11.47 GB | Download |
| Tessa-T1-32B.i1-Q2_K_S.gguf | GGUF | Q2_K_S | 10.70 GB | Download |
| Tessa-T1-32B.i1-Q3_K_L.gguf | GGUF | Q3_K_L | 16.06 GB | Download |
| Tessa-T1-32B.i1-Q3_K_M.gguf | GGUF | Q3_K_M | 14.84 GB | Download |
| Tessa-T1-32B.i1-Q3_K_S.gguf | GGUF | Q3_K_S | 13.40 GB | Download |
| Tessa-T1-32B.i1-Q4_0.gguf | GGUF | — | 17.43 GB | Download |
| Tessa-T1-32B.i1-Q4_1.gguf | GGUF | — | 19.22 GB | Download |
| Tessa-T1-32B.i1-Q4_K_M.gguf | GGUF | Q4_K_M | 18.49 GB | Download |
| Tessa-T1-32B.i1-Q4_K_S.gguf | GGUF | Q4_K_S | 17.49 GB | Download |
| Tessa-T1-32B.i1-Q5_K_M.gguf | GGUF | Q5_K_M | 21.66 GB | Download |
| Tessa-T1-32B.i1-Q5_K_S.gguf | GGUF | Q5_K_S | 21.08 GB | Download |
| Tessa-T1-32B.i1-Q6_K.gguf | GGUF | Q6_K | 25.04 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "Tesslate/Tessa-T1-32B",
"datasets": [
"Tesslate/Tessa-T1-Dataset"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "apache-2.0",
"mradermacher": {
"readme_rev": 1
},
"quantized_by": "mradermacher",
"tags": [
"text-generation-inference",
"transformers",
"qwen2",
"trl"
],
"frontmatter": {
"base_model": "Tesslate/Tessa-T1-32B",
"datasets": [
"Tesslate/Tessa-T1-Dataset"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "apache-2.0",
"mradermacher": [],
"quantized_by": "mradermacher",
"tags": [
"text-generation-inference",
"transformers",
"qwen2",
"trl"
]
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About weighted/imatrix quants of https://huggingface.co/Tesslate/Tessa-T1-32B ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/Tessa-T1-32B-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: Tesslate/Tessa-T1-32B\ndatasets:\n- Tesslate/Tessa-T1-Dataset\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n readme_rev: 1\nquantized_by: mradermacher\ntags:\n- text-generation-inference\n- transformers\n- qwen2\n- trl\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/Tesslate/Tessa-T1-32B\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#Tessa-T1-32B-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/Tessa-T1-32B-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/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-IQ1_S.gguf) | i1-IQ1_S | 7.4 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-IQ1_M.gguf) | i1-IQ1_M | 8.0 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 9.1 | |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 10.1 | |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-IQ2_S.gguf) | i1-IQ2_S | 10.5 | |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-IQ2_M.gguf) | i1-IQ2_M | 11.4 | |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-Q2_K_S.gguf) | i1-Q2_K_S | 11.6 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-Q2_K.gguf) | i1-Q2_K | 12.4 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 12.9 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 13.8 | |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 14.5 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-IQ3_S.gguf) | i1-IQ3_S | 14.5 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-IQ3_M.gguf) | i1-IQ3_M | 14.9 | |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 16.0 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 17.3 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 17.8 | |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-Q4_0.gguf) | i1-Q4_0 | 18.8 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 18.9 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 20.0 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-Q4_1.gguf) | i1-Q4_1 | 20.7 | |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 22.7 | |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 23.4 | |\n| [GGUF](https://huggingface.co/mradermacher/Tessa-T1-32B-i1-GGUF/resolve/main/Tessa-T1-32B.i1-Q6_K.gguf) | i1-Q6_K | 27.0 | 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",
"text-generation-inference",
"qwen2",
"trl",
"en",
"dataset:Tesslate/Tessa-T1-Dataset",
"base_model:Tesslate/Tessa-T1-32B",
"base_model:quantized:Tesslate/Tessa-T1-32B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
],
"likes": 0,
"downloads": 131,
"gated": false,
"private": false,
"last_modified": "2025-07-11T08:06:15.000Z",
"created_at": "2025-03-25T14:19:56.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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