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mradermacher/hy-mt1.5-7b-gguf Q5_K_M 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/hy-mt1.5-7b-gguf overview

About static quants of https://huggingface.co/tencent/HY-MT1.5-7B For a convenient overview and download list, visit our model page for this model. weighted/imatrix quants are available at https://huggingface.co/mradermacher/HY-MT1.5-7B-i1-GGUF

transformersgguftranslationzhenfrptesjatrruarkothitdevimsidtlhiplcsnlkmmyfaguurte
mradermacher/hy-mt1.5-7b-gguf visual
Downloads
1,271
Likes
4
Pipeline
translation
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

12 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
HY-MT1.5-7B.IQ4_XS.gguf GGUF IQ4_XS 3.92 GB Download
HY-MT1.5-7B.Q2_K.gguf GGUF Q2_K 2.80 GB Download
HY-MT1.5-7B.Q3_K_L.gguf GGUF Q3_K_L 3.81 GB Download
HY-MT1.5-7B.Q3_K_M.gguf GGUF Q3_K_M 3.53 GB Download
HY-MT1.5-7B.Q3_K_S.gguf GGUF Q3_K_S 3.20 GB Download
HY-MT1.5-7B.Q4_K_M.gguf GGUF Q4_K_M 4.31 GB Download
HY-MT1.5-7B.Q4_K_S.gguf GGUF Q4_K_S 4.09 GB Download
HY-MT1.5-7B.Q5_K_M.gguf GGUF Q5_K_M 5.00 GB Download
HY-MT1.5-7B.Q5_K_S.gguf GGUF Q5_K_S 4.88 GB Download
HY-MT1.5-7B.Q6_K.gguf GGUF Q6_K 5.74 GB Download
HY-MT1.5-7B.Q8_0.gguf GGUF 7.43 GB Download
HY-MT1.5-7B.f16.gguf GGUF F16 13.99 GB Download

Model Details Live

Model Slug
mradermacher/hy-mt1.5-7b-gguf
Author
mradermacher
Pipeline Task
translation
Library
transformers
Created
2025-12-30
Last Modified
2025-12-30
Gated
No
Private
No
HF SHA
f98156bb2d93963feeaa1576fde038ee3c857651
License
Unknown
Language
zh, en, fr, pt, es, ja, tr, ru, ar, ko, th, it, de, vi, ms, id, tl, hi, pl, cs, nl, km, my, fa, gu, ur, te, mr, he, bn, ta, uk, bo, kk, mn, ug
Base Model
tencent/HY-MT1.5-7B

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "tencent/HY-MT1.5-7B",
    "language": [
      "zh",
      "en",
      "fr",
      "pt",
      "es",
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    "library_name": "transformers",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "translation"
    ],
    "frontmatter": {
      "base_model": "tencent/HY-MT1.5-7B",
      "language": [
        "zh",
        "en",
        "fr",
        "pt",
        "es",
        "ja",
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      "library_name": "transformers",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "translation"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         static quants of https://huggingface.co/tencent/HY-MT1.5-7B  ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/HY-MT1.5-7B-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: tencent/HY-MT1.5-7B\nlanguage:\n- zh\n- en\n- fr\n- pt\n- es\n- ja\n- tr\n- ru\n- ar\n- ko\n- th\n- it\n- de\n- vi\n- ms\n- id\n- tl\n- hi\n- pl\n- cs\n- nl\n- km\n- my\n- fa\n- gu\n- ur\n- te\n- mr\n- he\n- bn\n- ta\n- uk\n- bo\n- kk\n- mn\n- ug\nlibrary_name: transformers\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- translation\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags:  -->\n<!-- ### quants:  x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->\n<!-- ### quants_skip:  -->\n<!-- ### skip_mmproj:  -->\nstatic quants of https://huggingface.co/tencent/HY-MT1.5-7B\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#HY-MT1.5-7B-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/HY-MT1.5-7B-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/HY-MT1.5-7B-GGUF/resolve/main/HY-MT1.5-7B.Q2_K.gguf) | Q2_K | 3.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/HY-MT1.5-7B-GGUF/resolve/main/HY-MT1.5-7B.Q3_K_S.gguf) | Q3_K_S | 3.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/HY-MT1.5-7B-GGUF/resolve/main/HY-MT1.5-7B.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/HY-MT1.5-7B-GGUF/resolve/main/HY-MT1.5-7B.Q3_K_L.gguf) | Q3_K_L | 4.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/HY-MT1.5-7B-GGUF/resolve/main/HY-MT1.5-7B.IQ4_XS.gguf) | IQ4_XS | 4.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/HY-MT1.5-7B-GGUF/resolve/main/HY-MT1.5-7B.Q4_K_S.gguf) | Q4_K_S | 4.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/HY-MT1.5-7B-GGUF/resolve/main/HY-MT1.5-7B.Q4_K_M.gguf) | Q4_K_M | 4.7 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/HY-MT1.5-7B-GGUF/resolve/main/HY-MT1.5-7B.Q5_K_S.gguf) | Q5_K_S | 5.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/HY-MT1.5-7B-GGUF/resolve/main/HY-MT1.5-7B.Q5_K_M.gguf) | Q5_K_M | 5.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/HY-MT1.5-7B-GGUF/resolve/main/HY-MT1.5-7B.Q6_K.gguf) | Q6_K | 6.3 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/HY-MT1.5-7B-GGUF/resolve/main/HY-MT1.5-7B.Q8_0.gguf) | Q8_0 | 8.1 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/HY-MT1.5-7B-GGUF/resolve/main/HY-MT1.5-7B.f16.gguf) | f16 | 15.1 | 16 bpw, overkill |\n\nHere is a handy graph by ikawrakow comparing some lower-quality quant\ntypes (lower is better):\n\n![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)\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": [
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    "base_model:tencent/HY-MT1.5-7B",
    "base_model:quantized:tencent/HY-MT1.5-7B",
    "endpoints_compatible",
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  ],
  "likes": 4,
  "downloads": 1271,
  "gated": false,
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  "last_modified": "2025-12-30T14:14:08.000Z",
  "created_at": "2025-12-30T13:23:56.000Z",
  "pipeline_tag": "translation",
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}
Source payload excerpt (from Hugging Face API)
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