Model Intelligence Sheet
mradermacher/vieneu-tts-i1-gguf overview
About weighted/imatrix quants of https://huggingface.co/pnnbao-ump/VieNeu-TTS For a convenient overview and download list, visit our model page for this model. static quants are available at https://huggingface.co/mradermacher/VieNeu-TTS-GGUF
Downloads
461
Likes
2
Pipeline
—
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
25 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| VieNeu-TTS.i1-IQ1_M.gguf | GGUF | IQ1_M | 364.65 MB | Download |
| VieNeu-TTS.i1-IQ1_S.gguf | GGUF | IQ1_S | 362.60 MB | Download |
| VieNeu-TTS.i1-IQ2_M.gguf | GGUF | IQ2_M | 374.78 MB | Download |
| VieNeu-TTS.i1-IQ2_S.gguf | GGUF | IQ2_S | 372.05 MB | Download |
| VieNeu-TTS.i1-IQ2_XS.gguf | GGUF | IQ2_XS | 370.78 MB | Download |
| VieNeu-TTS.i1-IQ2_XXS.gguf | GGUF | IQ2_XXS | 368.05 MB | Download |
| VieNeu-TTS.i1-IQ3_M.gguf | GGUF | IQ3_M | 388.28 MB | Download |
| VieNeu-TTS.i1-IQ3_S.gguf | GGUF | IQ3_S | 384.32 MB | Download |
| VieNeu-TTS.i1-IQ3_XS.gguf | GGUF | IQ3_XS | 384.32 MB | Download |
| VieNeu-TTS.i1-IQ3_XXS.gguf | GGUF | IQ3_XXS | 379.65 MB | Download |
| VieNeu-TTS.i1-IQ4_NL.gguf | GGUF | IQ4_NL | 397.73 MB | Download |
| VieNeu-TTS.i1-IQ4_XS.gguf | GGUF | IQ4_XS | 394.62 MB | Download |
| VieNeu-TTS.i1-Q2_K.gguf | GGUF | Q2_K | 384.32 MB | Download |
| VieNeu-TTS.i1-Q2_K_S.gguf | GGUF | Q2_K_S | 377.11 MB | Download |
| VieNeu-TTS.i1-Q3_K_L.gguf | GGUF | Q3_K_L | 413.65 MB | Download |
| VieNeu-TTS.i1-Q3_K_M.gguf | GGUF | Q3_K_M | 400.40 MB | Download |
| VieNeu-TTS.i1-Q3_K_S.gguf | GGUF | Q3_K_S | 383.99 MB | Download |
| VieNeu-TTS.i1-Q4_0.gguf | GGUF | — | 398.02 MB | Download |
| VieNeu-TTS.i1-Q4_1.gguf | GGUF | — | 418.57 MB | Download |
| VieNeu-TTS.i1-Q4_K_M.gguf | GGUF | Q4_K_M | 440.78 MB | Download |
| VieNeu-TTS.i1-Q4_K_S.gguf | GGUF | Q4_K_S | 429.02 MB | Download |
| VieNeu-TTS.i1-Q5_K_M.gguf | GGUF | Q5_K_M | 462.03 MB | Download |
| VieNeu-TTS.i1-Q5_K_S.gguf | GGUF | Q5_K_S | 454.99 MB | Download |
| VieNeu-TTS.i1-Q6_K.gguf | GGUF | Q6_K | 543.71 MB | Download |
| VieNeu-TTS.imatrix.gguf | GGUF | — | 0.96 MB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "pnnbao-ump/VieNeu-TTS",
"datasets": [
"pnnbao-ump/VieNeu-TTS-1000h",
"pnnbao-ump/VieNeu-TTS-140h"
],
"language": [
"vi"
],
"library_name": "transformers",
"license": "apache-2.0",
"mradermacher": {
"readme_rev": 1
},
"quantized_by": "mradermacher",
"frontmatter": {
"base_model": "pnnbao-ump/VieNeu-TTS",
"datasets": [
"pnnbao-ump/VieNeu-TTS-1000h",
"pnnbao-ump/VieNeu-TTS-140h"
],
"language": [
"vi"
],
"library_name": "transformers",
"license": "apache-2.0",
"mradermacher": [],
"quantized_by": "mradermacher"
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About weighted/imatrix quants of https://huggingface.co/pnnbao-ump/VieNeu-TTS ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/VieNeu-TTS-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: pnnbao-ump/VieNeu-TTS\ndatasets:\n- pnnbao-ump/VieNeu-TTS-1000h\n- pnnbao-ump/VieNeu-TTS-140h\nlanguage:\n- vi\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n readme_rev: 1\nquantized_by: mradermacher\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type: -->\n<!-- ### tags: nicoboss -->\n<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->\n<!-- ### quants_skip: -->\n<!-- ### skip_mmproj: -->\nweighted/imatrix quants of https://huggingface.co/pnnbao-ump/VieNeu-TTS\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#VieNeu-TTS-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/VieNeu-TTS-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/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-IQ1_S.gguf) | i1-IQ1_S | 0.5 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-IQ1_M.gguf) | i1-IQ1_M | 0.5 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-IQ2_XS.gguf) | i1-IQ2_XS | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-IQ2_S.gguf) | i1-IQ2_S | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-IQ2_M.gguf) | i1-IQ2_M | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-Q2_K_S.gguf) | i1-Q2_K_S | 0.5 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 0.5 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-Q3_K_S.gguf) | i1-Q3_K_S | 0.5 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-IQ3_S.gguf) | i1-IQ3_S | 0.5 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-IQ3_XS.gguf) | i1-IQ3_XS | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-Q2_K.gguf) | i1-Q2_K | 0.5 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-IQ3_M.gguf) | i1-IQ3_M | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-IQ4_XS.gguf) | i1-IQ4_XS | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-IQ4_NL.gguf) | i1-IQ4_NL | 0.5 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-Q4_0.gguf) | i1-Q4_0 | 0.5 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-Q3_K_M.gguf) | i1-Q3_K_M | 0.5 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-Q3_K_L.gguf) | i1-Q3_K_L | 0.5 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-Q4_1.gguf) | i1-Q4_1 | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-Q4_K_S.gguf) | i1-Q4_K_S | 0.5 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-Q4_K_M.gguf) | i1-Q4_K_M | 0.6 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-Q5_K_S.gguf) | i1-Q5_K_S | 0.6 | |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-Q5_K_M.gguf) | i1-Q5_K_M | 0.6 | |\n| [GGUF](https://huggingface.co/mradermacher/VieNeu-TTS-i1-GGUF/resolve/main/VieNeu-TTS.i1-Q6_K.gguf) | i1-Q6_K | 0.7 | 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",
"vi",
"dataset:pnnbao-ump/VieNeu-TTS-1000h",
"dataset:pnnbao-ump/VieNeu-TTS-140h",
"base_model:pnnbao-ump/VieNeu-TTS",
"base_model:quantized:pnnbao-ump/VieNeu-TTS",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix"
],
"likes": 2,
"downloads": 461,
"gated": false,
"private": false,
"last_modified": "2026-01-11T02:43:24.000Z",
"created_at": "2025-11-09T19:24:41.000Z",
"pipeline_tag": "",
"library_name": "transformers"
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Source payload excerpt (from Hugging Face API)
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