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mradermacher/albert_wesker-1b-i1-gguf IQ3_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/albert_wesker-1b-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/UmbrellaInc/AlbertWesker-1B *For a convenient overview and download list, visit our model page for this model.* static quants are available at https://huggingface.co/mradermacher/AlbertWesker-1B-GGUF

transformersggufnpcroleplayrpnsfwlow-refusalsuncensoredhereticabliteratedunslothfinetuneall use casesbfloat16creativecreative writingfiction writingplot generationsub-plot generationstory generationscene continuestorytellingfiction storyscience fictionromanceslice of lifeall genresstorywritingvivid prosing
mradermacher/albert_wesker-1b-i1-gguf visual
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0
Pipeline
text-generation
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

25 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
Albert_Wesker-1B.i1-IQ1_M.gguf GGUF IQ1_M 613.68 MB Download
Albert_Wesker-1B.i1-IQ1_S.gguf GGUF IQ1_S 609.59 MB Download
Albert_Wesker-1B.i1-IQ2_M.gguf GGUF IQ2_M 638.76 MB Download
Albert_Wesker-1B.i1-IQ2_S.gguf GGUF IQ2_S 633.30 MB Download
Albert_Wesker-1B.i1-IQ2_XS.gguf GGUF IQ2_XS 626.88 MB Download
Albert_Wesker-1B.i1-IQ2_XXS.gguf GGUF IQ2_XXS 620.50 MB Download
Albert_Wesker-1B.i1-IQ3_M.gguf GGUF IQ3_M 664.77 MB Download
Albert_Wesker-1B.i1-IQ3_S.gguf GGUF IQ3_S 657.86 MB Download
Albert_Wesker-1B.i1-IQ3_XS.gguf GGUF IQ3_XS 657.86 MB Download
Albert_Wesker-1B.i1-IQ3_XXS.gguf GGUF IQ3_XXS 648.61 MB Download
Albert_Wesker-1B.i1-IQ4_NL.gguf GGUF IQ4_NL 688.43 MB Download
Albert_Wesker-1B.i1-IQ4_XS.gguf GGUF IQ4_XS 681.34 MB Download
Albert_Wesker-1B.i1-Q2_K.gguf GGUF Q2_K 657.86 MB Download
Albert_Wesker-1B.i1-Q2_K_S.gguf GGUF Q2_K_S 640.18 MB Download
Albert_Wesker-1B.i1-Q3_K_L.gguf GGUF Q3_K_L 716.76 MB Download
Albert_Wesker-1B.i1-Q3_K_M.gguf GGUF Q3_K_M 688.96 MB Download
Albert_Wesker-1B.i1-Q3_K_S.gguf GGUF Q3_K_S 656.95 MB Download
Albert_Wesker-1B.i1-Q4_0.gguf GGUF 688.48 MB Download
Albert_Wesker-1B.i1-Q4_1.gguf GGUF 728.65 MB Download
Albert_Wesker-1B.i1-Q4_K_M.gguf GGUF Q4_K_M 768.72 MB Download
Albert_Wesker-1B.i1-Q4_K_S.gguf GGUF Q4_K_S 744.82 MB Download
Albert_Wesker-1B.i1-Q5_K_M.gguf GGUF Q5_K_M 811.91 MB Download
Albert_Wesker-1B.i1-Q5_K_S.gguf GGUF Q5_K_S 797.66 MB Download
Albert_Wesker-1B.i1-Q6_K.gguf GGUF Q6_K 964.87 MB Download
Albert_Wesker-1B.imatrix.gguf GGUF 1.39 MB Download

Model Details Live

Model Slug
mradermacher/albert_wesker-1b-i1-gguf
Author
mradermacher
Pipeline Task
text-generation
Library
transformers
Created
2026-03-07
Last Modified
2026-03-08
Gated
No
Private
No
HF SHA
97d3f7be29d60f399359541755ef333d2ce56223
License
gemma
Language
tr, ar, af, az, es, en, el, ro, ru, rm, th, uk, uz, pl, pt, fa, sk, sl, da, de, nl, fr, fi, ka, hi, hu, hy, ja, kk, kn, ko, ku, ky, la, lb, id, is, it, zh, cs, vi, be, bg, bs, ne, mn
Base Model
UmbrellaInc/Albert_Wesker-1B

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "UmbrellaInc/Albert_Wesker-1B",
    "datasets": [
      "TeichAI/glm-4.7-2000x",
      "chimbiwide/RolePlay-NPCv2",
      "berkeruveyik/toxic-speech-annotated-dataset",
      "mlabonne/FineTome-100k",
      "ITCL/FineTomeOs",
      "Gryphe/ChatGPT-4o-Writing-Prompts",
      "dongguanting/ARPO-SFT-54K",
      "GreenerPastures/All-Your-Base-Full",
      "Gryphe/Opus-WritingPrompts",
      "HuggingFaceH4/MATH-500",
      "mlabonne/smoltalk-flat",
      "mlabonne/natural_reasoning-formatted",
      "OpenSPG/KAG-Thinker-training-dataset",
      "uclanlp/Brief-Pro",
      "CognitiveKernel/CognitiveKernel-Pro-SFT",
      "SuperbEmphasis/Claude-4.0-DeepSeek-R1-RP-SFWish",
      "QuixiAI/dolphin-r1",
      "mlabonne/lmsys-arena-human-sft-55k"
    ],
    "language": [
      "tr",
      "ar",
      "af",
      "az",
      "es",
      "en",
      "el",
      "ro",
      "ru",
      "rm",
      "th",
      "uk",
      "uz",
      "pl",
      "pt",
      "fa",
      "sk",
      "sl",
      "da",
      "de",
      "nl",
      "fr",
      "fi",
      "ka",
      "hi",
      "hu",
      "hy",
      "ja",
      "kk",
      "kn",
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    ],
    "library_name": "transformers",
    "license": "gemma",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "npc",
      "roleplay",
      "rp",
      "nsfw",
      "low-refusals",
      "uncensored",
      "heretic",
      "abliterated",
      "unsloth",
      "finetune",
      "all use cases",
      "bfloat16",
      "creative",
      "creative writing",
      "fiction writing",
      "plot generation",
      "sub-plot generation",
      "fiction writing",
      "story generation",
      "scene continue",
      "storytelling",
      "fiction story",
      "science fiction",
      "romance",
      "slice of life",
      "all genres",
      "story",
      "writing",
      "vivid prosing",
      "vivid writing",
      "fiction",
      "text-generation",
      "transformers",
      "safetensors",
      "gemma3",
      "mergekit",
      "karcher mean",
      "uncensored",
      "heretic",
      "roleplay",
      "nsfw",
      "virus",
      "t-virus",
      "low-end",
      "conversational",
      "think",
      "Not-For-All-Audiences"
    ],
    "frontmatter": {
      "base_model": "UmbrellaInc/Albert_Wesker-1B",
      "datasets": [
        "TeichAI/glm-4.7-2000x",
        "chimbiwide/RolePlay-NPCv2",
        "berkeruveyik/toxic-speech-annotated-dataset",
        "mlabonne/FineTome-100k",
        "ITCL/FineTomeOs",
        "Gryphe/ChatGPT-4o-Writing-Prompts",
        "dongguanting/ARPO-SFT-54K",
        "GreenerPastures/All-Your-Base-Full",
        "Gryphe/Opus-WritingPrompts",
        "HuggingFaceH4/MATH-500",
        "mlabonne/smoltalk-flat",
        "mlabonne/natural_reasoning-formatted",
        "OpenSPG/KAG-Thinker-training-dataset",
        "uclanlp/Brief-Pro",
        "CognitiveKernel/CognitiveKernel-Pro-SFT",
        "SuperbEmphasis/Claude-4.0-DeepSeek-R1-RP-SFWish",
        "QuixiAI/dolphin-r1",
        "mlabonne/lmsys-arena-human-sft-55k"
      ],
      "language": [
        "tr",
        "ar",
        "af",
        "az",
        "es",
        "en",
        "el",
        "ro",
        "ru",
        "rm",
        "th",
        "uk",
        "uz",
        "pl",
        "pt",
        "fa",
        "sk",
        "sl",
        "da",
        "de",
        "nl",
        "fr",
        "fi",
        "ka",
        "hi",
        "hu",
        "hy",
        "ja",
        "kk",
        "kn",
        "ko",
        "ku",
        "ky",
        "la",
        "lb",
        "id",
        "is",
        "it",
        "zh",
        "cs",
        "vi",
        "be",
        "bg",
        "bs",
        "ne",
        "mn"
      ],
      "library_name": "transformers",
      "license": "gemma",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "npc",
        "roleplay",
        "rp",
        "nsfw",
        "low-refusals",
        "uncensored",
        "heretic",
        "abliterated",
        "unsloth",
        "finetune",
        "all use cases",
        "bfloat16",
        "creative",
        "creative writing",
        "fiction writing",
        "plot generation",
        "sub-plot generation",
        "fiction writing",
        "story generation",
        "scene continue",
        "storytelling",
        "fiction story",
        "science fiction",
        "romance",
        "slice of life",
        "all genres",
        "story",
        "writing",
        "vivid prosing",
        "vivid writing",
        "fiction",
        "text-generation",
        "transformers",
        "safetensors",
        "gemma3",
        "mergekit",
        "karcher mean",
        "uncensored",
        "heretic",
        "roleplay",
        "nsfw",
        "virus",
        "t-virus",
        "low-end",
        "conversational",
        "think",
        "Not-For-All-Audiences"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         weighted/imatrix quants of https://huggingface.co/UmbrellaInc/Albert_Wesker-1B  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/Albert_Wesker-1B-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: UmbrellaInc/Albert_Wesker-1B\ndatasets:\n- TeichAI/glm-4.7-2000x\n- chimbiwide/RolePlay-NPCv2\n- berkeruveyik/toxic-speech-annotated-dataset\n- mlabonne/FineTome-100k\n- ITCL/FineTomeOs\n- Gryphe/ChatGPT-4o-Writing-Prompts\n- dongguanting/ARPO-SFT-54K\n- GreenerPastures/All-Your-Base-Full\n- Gryphe/Opus-WritingPrompts\n- HuggingFaceH4/MATH-500\n- mlabonne/smoltalk-flat\n- mlabonne/natural_reasoning-formatted\n- OpenSPG/KAG-Thinker-training-dataset\n- uclanlp/Brief-Pro\n- CognitiveKernel/CognitiveKernel-Pro-SFT\n- SuperbEmphasis/Claude-4.0-DeepSeek-R1-RP-SFWish\n- QuixiAI/dolphin-r1\n- mlabonne/lmsys-arena-human-sft-55k\nlanguage:\n- tr\n- ar\n- af\n- az\n- es\n- en\n- el\n- ro\n- ru\n- rm\n- th\n- uk\n- uz\n- pl\n- pt\n- fa\n- sk\n- sl\n- da\n- de\n- nl\n- fr\n- fi\n- ka\n- hi\n- hu\n- hy\n- ja\n- kk\n- kn\n- ko\n- ku\n- ky\n- la\n- lb\n- id\n- is\n- it\n- zh\n- cs\n- vi\n- be\n- bg\n- bs\n- ne\n- mn\nlibrary_name: transformers\nlicense: gemma\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- npc\n- roleplay\n- rp\n- nsfw\n- low-refusals\n- uncensored\n- heretic\n- abliterated\n- unsloth\n- finetune\n- all use cases\n- bfloat16\n- creative\n- creative writing\n- fiction writing\n- plot generation\n- sub-plot generation\n- fiction writing\n- story generation\n- scene continue\n- storytelling\n- fiction story\n- science fiction\n- romance\n- slice of life\n- all genres\n- story\n- writing\n- vivid prosing\n- vivid writing\n- fiction\n- text-generation\n- transformers\n- safetensors\n- gemma3\n- mergekit\n- karcher mean\n- uncensored\n- heretic\n- roleplay\n- nsfw\n- virus\n- t-virus\n- low-end\n- conversational\n- think\n- Not-For-All-Audiences\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/UmbrellaInc/Albert_Wesker-1B\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#Albert_Wesker-1B-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/Albert_Wesker-1B-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/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-IQ1_S.gguf) | i1-IQ1_S | 0.7 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-IQ1_M.gguf) | i1-IQ1_M | 0.7 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 0.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 0.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-IQ2_S.gguf) | i1-IQ2_S | 0.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-IQ2_M.gguf) | i1-IQ2_M | 0.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-Q2_K_S.gguf) | i1-Q2_K_S | 0.8 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 0.8 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 0.8 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-IQ3_S.gguf) | i1-IQ3_S | 0.8 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 0.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-Q2_K.gguf) | i1-Q2_K | 0.8 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-IQ3_M.gguf) | i1-IQ3_M | 0.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 0.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-IQ4_NL.gguf) | i1-IQ4_NL | 0.8 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-Q4_0.gguf) | i1-Q4_0 | 0.8 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 0.8 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 0.9 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-Q4_1.gguf) | i1-Q4_1 | 0.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 0.9 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 0.9 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 0.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 1.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Albert_Wesker-1B-i1-GGUF/resolve/main/Albert_Wesker-1B.i1-Q6_K.gguf) | i1-Q6_K | 1.1 | practically like static Q6_K |\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. 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",
    "npc",
    "roleplay",
    "rp",
    "nsfw",
    "low-refusals",
    "uncensored",
    "heretic",
    "abliterated",
    "unsloth",
    "finetune",
    "all use cases",
    "bfloat16",
    "creative",
    "creative writing",
    "fiction writing",
    "plot generation",
    "sub-plot generation",
    "story generation",
    "scene continue",
    "storytelling",
    "fiction story",
    "science fiction",
    "romance",
    "slice of life",
    "all genres",
    "story",
    "writing",
    "vivid prosing",
    "vivid writing",
    "fiction",
    "text-generation",
    "safetensors",
    "gemma3",
    "mergekit",
    "karcher mean",
    "virus",
    "t-virus",
    "low-end",
    "conversational",
    "think",
    "Not-For-All-Audiences",
    "tr",
    "ar",
    "af",
    "az",
    "es",
    "en",
    "el",
    "ro",
    "ru",
    "rm",
    "th",
    "uk",
    "uz",
    "pl",
    "pt",
    "fa",
    "sk",
    "sl",
    "da",
    "de",
    "nl",
    "fr",
    "fi",
    "ka",
    "hi",
    "hu",
    "hy",
    "ja",
    "kk",
    "kn",
    "ko",
    "ku",
    "ky",
    "la",
    "lb",
    "id",
    "is",
    "it",
    "zh",
    "cs",
    "vi",
    "be",
    "bg",
    "bs",
    "ne",
    "mn",
    "dataset:TeichAI/glm-4.7-2000x",
    "dataset:chimbiwide/RolePlay-NPCv2",
    "dataset:berkeruveyik/toxic-speech-annotated-dataset",
    "dataset:mlabonne/FineTome-100k",
    "dataset:ITCL/FineTomeOs",
    "dataset:Gryphe/ChatGPT-4o-Writing-Prompts",
    "dataset:dongguanting/ARPO-SFT-54K",
    "dataset:GreenerPastures/All-Your-Base-Full",
    "dataset:Gryphe/Opus-WritingPrompts",
    "dataset:HuggingFaceH4/MATH-500",
    "dataset:mlabonne/smoltalk-flat",
    "dataset:mlabonne/natural_reasoning-formatted",
    "dataset:OpenSPG/KAG-Thinker-training-dataset",
    "dataset:uclanlp/Brief-Pro",
    "dataset:CognitiveKernel/CognitiveKernel-Pro-SFT",
    "dataset:SuperbEmphasis/Claude-4.0-DeepSeek-R1-RP-SFWish",
    "dataset:QuixiAI/dolphin-r1",
    "dataset:mlabonne/lmsys-arena-human-sft-55k",
    "base_model:UmbrellaInc/Albert_Wesker-1B",
    "base_model:quantized:UmbrellaInc/Albert_Wesker-1B",
    "license:gemma",
    "endpoints_compatible",
    "region:us",
    "imatrix"
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Source payload excerpt (from Hugging Face API)
{
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