Model Intelligence Sheet
mradermacher/spydazweb_ai_lcars_humanization_003-gguf overview
About static quants of https://huggingface.co/LeroyDyer/SpydazWebAILCARSHumanization003 weighted/imatrix quants are available at https://huggingface.co/mradermacher/SpydazWebAILCARSHumanization003-i1-GGUF
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| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| SpydazWeb_AI_LCARS_Humanization_003.IQ4_XS.gguf | GGUF | IQ4_XS | 3.67 GB | Download |
| SpydazWeb_AI_LCARS_Humanization_003.Q2_K.gguf | GGUF | Q2_K | 2.53 GB | Download |
| SpydazWeb_AI_LCARS_Humanization_003.Q3_K_L.gguf | GGUF | Q3_K_L | 3.56 GB | Download |
| SpydazWeb_AI_LCARS_Humanization_003.Q3_K_M.gguf | GGUF | Q3_K_M | 3.28 GB | Download |
| SpydazWeb_AI_LCARS_Humanization_003.Q3_K_S.gguf | GGUF | Q3_K_S | 2.95 GB | Download |
| SpydazWeb_AI_LCARS_Humanization_003.Q4_K_M.gguf | GGUF | Q4_K_M | 4.07 GB | Download |
| SpydazWeb_AI_LCARS_Humanization_003.Q4_K_S.gguf | GGUF | Q4_K_S | 3.86 GB | Download |
| SpydazWeb_AI_LCARS_Humanization_003.Q5_K_M.gguf | GGUF | Q5_K_M | 4.78 GB | Download |
| SpydazWeb_AI_LCARS_Humanization_003.Q5_K_S.gguf | GGUF | Q5_K_S | 4.65 GB | Download |
| SpydazWeb_AI_LCARS_Humanization_003.Q6_K.gguf | GGUF | Q6_K | 5.53 GB | Download |
| SpydazWeb_AI_LCARS_Humanization_003.Q8_0.gguf | GGUF | — | 7.17 GB | Download |
| SpydazWeb_AI_LCARS_Humanization_003.f16.gguf | GGUF | F16 | 13.49 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "LeroyDyer/SpydazWeb_AI_LCARS_Humanization_003",
"datasets": [
"gretelai/synthetic_text_to_sql",
"HuggingFaceTB/cosmopedia",
"teknium/OpenHermes-2.5",
"Open-Orca/SlimOrca",
"Severian/Internal-Knowledge-Map",
"Open-Orca/OpenOrca",
"cognitivecomputations/dolphin-coder",
"databricks/databricks-dolly-15k",
"yahma/alpaca-cleaned",
"uonlp/CulturaX",
"mwitiderrick/SwahiliPlatypus",
"NexusAI-tddi/OpenOrca-tr-1-million-sharegpt",
"Vezora/Open-Critic-GPT",
"verifiers-for-code/deepseek_plans_test",
"meta-math/MetaMathQA",
"KbsdJames/Omni-MATH",
"swahili",
"Rogendo/English-Swahili-Sentence-Pairs",
"ise-uiuc/Magicoder-Evol-Instruct-110K",
"meta-math/MetaMathQA",
"abacusai/ARC_DPO_FewShot",
"abacusai/MetaMath_DPO_FewShot",
"abacusai/HellaSwag_DPO_FewShot",
"HaltiaAI/Her-The-Movie-Samantha-and-Theodore-Dataset",
"HuggingFaceFW/fineweb",
"occiglot/occiglot-fineweb-v0.5",
"omi-health/medical-dialogue-to-soap-summary",
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"ruslanmv/ai-medical-dataset",
"Shekswess/medical_llama3_instruct_dataset_short",
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"PatronusAI/financebench",
"takala/financial_phrasebank",
"Replete-AI/code_bagel",
"athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW",
"IlyaGusev/gpt_roleplay_realm",
"rickRossie/bluemoon_roleplay_chat_data_300k_messages",
"jtatman/hypnosis_dataset",
"Hypersniper/philosophy_dialogue",
"Locutusque/function-calling-chatml",
"bible-nlp/biblenlp-corpus",
"DatadudeDev/Bible",
"Helsinki-NLP/bible_para",
"HausaNLP/AfriSenti-Twitter",
"aixsatoshi/Chat-with-cosmopedia",
"xz56/react-llama",
"BeIR/hotpotqa",
"YBXL/medical_book_train_filtered",
"SkunkworksAI/reasoning-0.01",
"THUDM/LongWriter-6k",
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"frontmatter": {
"base_model": "LeroyDyer/SpydazWeb_AI_LCARS_Humanization_003",
"datasets": [
"gretelai/synthetic_text_to_sql",
"HuggingFaceTB/cosmopedia",
"teknium/OpenHermes-2.5",
"Open-Orca/SlimOrca",
"Severian/Internal-Knowledge-Map",
"Open-Orca/OpenOrca",
"cognitivecomputations/dolphin-coder",
"databricks/databricks-dolly-15k",
"yahma/alpaca-cleaned",
"uonlp/CulturaX",
"mwitiderrick/SwahiliPlatypus",
"NexusAI-tddi/OpenOrca-tr-1-million-sharegpt",
"Vezora/Open-Critic-GPT",
"verifiers-for-code/deepseek_plans_test",
"meta-math/MetaMathQA",
"KbsdJames/Omni-MATH",
"swahili",
"Rogendo/English-Swahili-Sentence-Pairs",
"ise-uiuc/Magicoder-Evol-Instruct-110K",
"meta-math/MetaMathQA",
"abacusai/ARC_DPO_FewShot",
"abacusai/MetaMath_DPO_FewShot",
"abacusai/HellaSwag_DPO_FewShot",
"HaltiaAI/Her-The-Movie-Samantha-and-Theodore-Dataset",
"HuggingFaceFW/fineweb",
"occiglot/occiglot-fineweb-v0.5",
"omi-health/medical-dialogue-to-soap-summary",
"keivalya/MedQuad-MedicalQnADataset",
"ruslanmv/ai-medical-dataset",
"Shekswess/medical_llama3_instruct_dataset_short",
"ShenRuililin/MedicalQnA",
"virattt/financial-qa-10K",
"PatronusAI/financebench",
"takala/financial_phrasebank",
"Replete-AI/code_bagel",
"athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW",
"IlyaGusev/gpt_roleplay_realm",
"rickRossie/bluemoon_roleplay_chat_data_300k_messages",
"jtatman/hypnosis_dataset",
"Hypersniper/philosophy_dialogue",
"Locutusque/function-calling-chatml",
"bible-nlp/biblenlp-corpus",
"DatadudeDev/Bible",
"Helsinki-NLP/bible_para",
"HausaNLP/AfriSenti-Twitter",
"aixsatoshi/Chat-with-cosmopedia",
"xz56/react-llama",
"BeIR/hotpotqa",
"YBXL/medical_book_train_filtered",
"SkunkworksAI/reasoning-0.01",
"THUDM/LongWriter-6k",
"WhiteRabbitNeo/WRN-Chapter-1",
"WhiteRabbitNeo/Code-Functions-Level-Cyber",
"WhiteRabbitNeo/Code-Functions-Level-General"
],
"language": [
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"sw",
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"xh",
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"library_name": "transformers",
"license": "mit",
"quantized_by": "mradermacher",
"tags": [
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"merge",
"Mistral_Star",
"Mistral_Quiet",
"Mistral",
"Mixtral",
"Question-Answer",
"Token-Classification",
"Sequence-Classification",
"SpydazWeb-AI",
"chemistry",
"biology",
"legal",
"code",
"climate",
"medical",
"LCARS_AI_StarTrek_Computer",
"text-generation-inference",
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"visual-spacial-sketchpad",
"alpha-mind",
"knowledge-graph",
"entity-detection",
"encyclopedia",
"wikipedia",
"stack-exchange",
"Reddit",
"Cyber-series",
"MegaMind",
"Cybertron",
"SpydazWeb",
"Spydaz",
"LCARS",
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"African-Model",
"Ancient-One"
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},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/LeroyDyer/SpydazWeb_AI_LCARS_Humanization_003 weighted/imatrix quants are available at https://huggingface.co/mradermacher/SpydazWeb_AI_LCARS_Humanization_003-i1-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: LeroyDyer/SpydazWeb_AI_LCARS_Humanization_003\ndatasets:\n- gretelai/synthetic_text_to_sql\n- HuggingFaceTB/cosmopedia\n- teknium/OpenHermes-2.5\n- Open-Orca/SlimOrca\n- Severian/Internal-Knowledge-Map\n- Open-Orca/OpenOrca\n- cognitivecomputations/dolphin-coder\n- databricks/databricks-dolly-15k\n- yahma/alpaca-cleaned\n- uonlp/CulturaX\n- mwitiderrick/SwahiliPlatypus\n- NexusAI-tddi/OpenOrca-tr-1-million-sharegpt\n- Vezora/Open-Critic-GPT\n- verifiers-for-code/deepseek_plans_test\n- meta-math/MetaMathQA\n- KbsdJames/Omni-MATH\n- swahili\n- Rogendo/English-Swahili-Sentence-Pairs\n- ise-uiuc/Magicoder-Evol-Instruct-110K\n- meta-math/MetaMathQA\n- abacusai/ARC_DPO_FewShot\n- abacusai/MetaMath_DPO_FewShot\n- abacusai/HellaSwag_DPO_FewShot\n- HaltiaAI/Her-The-Movie-Samantha-and-Theodore-Dataset\n- HuggingFaceFW/fineweb\n- occiglot/occiglot-fineweb-v0.5\n- omi-health/medical-dialogue-to-soap-summary\n- keivalya/MedQuad-MedicalQnADataset\n- ruslanmv/ai-medical-dataset\n- Shekswess/medical_llama3_instruct_dataset_short\n- ShenRuililin/MedicalQnA\n- virattt/financial-qa-10K\n- PatronusAI/financebench\n- takala/financial_phrasebank\n- Replete-AI/code_bagel\n- athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW\n- IlyaGusev/gpt_roleplay_realm\n- rickRossie/bluemoon_roleplay_chat_data_300k_messages\n- jtatman/hypnosis_dataset\n- Hypersniper/philosophy_dialogue\n- Locutusque/function-calling-chatml\n- bible-nlp/biblenlp-corpus\n- DatadudeDev/Bible\n- Helsinki-NLP/bible_para\n- HausaNLP/AfriSenti-Twitter\n- aixsatoshi/Chat-with-cosmopedia\n- xz56/react-llama\n- BeIR/hotpotqa\n- YBXL/medical_book_train_filtered\n- SkunkworksAI/reasoning-0.01\n- THUDM/LongWriter-6k\n- WhiteRabbitNeo/WRN-Chapter-1\n- WhiteRabbitNeo/Code-Functions-Level-Cyber\n- WhiteRabbitNeo/Code-Functions-Level-General\nlanguage:\n- en\n- sw\n- ig\n- so\n- es\n- ca\n- xh\n- zu\n- ha\n- tw\n- af\n- hi\n- bm\n- su\nlibrary_name: transformers\nlicense: mit\nquantized_by: mradermacher\ntags:\n- mergekit\n- merge\n- Mistral_Star\n- Mistral_Quiet\n- Mistral\n- Mixtral\n- Question-Answer\n- Token-Classification\n- Sequence-Classification\n- SpydazWeb-AI\n- chemistry\n- biology\n- legal\n- code\n- climate\n- medical\n- LCARS_AI_StarTrek_Computer\n- text-generation-inference\n- chain-of-thought\n- tree-of-knowledge\n- forest-of-thoughts\n- visual-spacial-sketchpad\n- alpha-mind\n- knowledge-graph\n- entity-detection\n- encyclopedia\n- wikipedia\n- stack-exchange\n- Reddit\n- Cyber-series\n- MegaMind\n- Cybertron\n- SpydazWeb\n- Spydaz\n- LCARS\n- star-trek\n- mega-transformers\n- Mulit-Mega-Merge\n- Multi-Lingual\n- Afro-Centric\n- African-Model\n- Ancient-One\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/LeroyDyer/SpydazWeb_AI_LCARS_Humanization_003\n\n<!-- provided-files -->\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/SpydazWeb_AI_LCARS_Humanization_003-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/SpydazWeb_AI_LCARS_Humanization_003-GGUF/resolve/main/SpydazWeb_AI_LCARS_Humanization_003.Q2_K.gguf) | Q2_K | 2.8 | |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_LCARS_Humanization_003-GGUF/resolve/main/SpydazWeb_AI_LCARS_Humanization_003.Q3_K_S.gguf) | Q3_K_S | 3.3 | |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_LCARS_Humanization_003-GGUF/resolve/main/SpydazWeb_AI_LCARS_Humanization_003.Q3_K_M.gguf) | Q3_K_M | 3.6 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_LCARS_Humanization_003-GGUF/resolve/main/SpydazWeb_AI_LCARS_Humanization_003.Q3_K_L.gguf) | Q3_K_L | 3.9 | |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_LCARS_Humanization_003-GGUF/resolve/main/SpydazWeb_AI_LCARS_Humanization_003.IQ4_XS.gguf) | IQ4_XS | 4.0 | |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_LCARS_Humanization_003-GGUF/resolve/main/SpydazWeb_AI_LCARS_Humanization_003.Q4_K_S.gguf) | Q4_K_S | 4.2 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_LCARS_Humanization_003-GGUF/resolve/main/SpydazWeb_AI_LCARS_Humanization_003.Q4_K_M.gguf) | Q4_K_M | 4.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_LCARS_Humanization_003-GGUF/resolve/main/SpydazWeb_AI_LCARS_Humanization_003.Q5_K_S.gguf) | Q5_K_S | 5.1 | |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_LCARS_Humanization_003-GGUF/resolve/main/SpydazWeb_AI_LCARS_Humanization_003.Q5_K_M.gguf) | Q5_K_M | 5.2 | |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_LCARS_Humanization_003-GGUF/resolve/main/SpydazWeb_AI_LCARS_Humanization_003.Q6_K.gguf) | Q6_K | 6.0 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_LCARS_Humanization_003-GGUF/resolve/main/SpydazWeb_AI_LCARS_Humanization_003.Q8_0.gguf) | Q8_0 | 7.8 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_LCARS_Humanization_003-GGUF/resolve/main/SpydazWeb_AI_LCARS_Humanization_003.f16.gguf) | f16 | 14.6 | 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": [
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"dataset:gretelai/synthetic_text_to_sql",
"dataset:HuggingFaceTB/cosmopedia",
"dataset:teknium/OpenHermes-2.5",
"dataset:Open-Orca/SlimOrca",
"dataset:Severian/Internal-Knowledge-Map",
"dataset:Open-Orca/OpenOrca",
"dataset:cognitivecomputations/dolphin-coder",
"dataset:databricks/databricks-dolly-15k",
"dataset:yahma/alpaca-cleaned",
"dataset:uonlp/CulturaX",
"dataset:mwitiderrick/SwahiliPlatypus",
"dataset:NexusAI-tddi/OpenOrca-tr-1-million-sharegpt",
"dataset:Vezora/Open-Critic-GPT",
"dataset:verifiers-for-code/deepseek_plans_test",
"dataset:meta-math/MetaMathQA",
"dataset:KbsdJames/Omni-MATH",
"dataset:swahili",
"dataset:Rogendo/English-Swahili-Sentence-Pairs",
"dataset:ise-uiuc/Magicoder-Evol-Instruct-110K",
"dataset:abacusai/ARC_DPO_FewShot",
"dataset:abacusai/MetaMath_DPO_FewShot",
"dataset:abacusai/HellaSwag_DPO_FewShot",
"dataset:HaltiaAI/Her-The-Movie-Samantha-and-Theodore-Dataset",
"dataset:HuggingFaceFW/fineweb",
"dataset:occiglot/occiglot-fineweb-v0.5",
"dataset:omi-health/medical-dialogue-to-soap-summary",
"dataset:keivalya/MedQuad-MedicalQnADataset",
"dataset:ruslanmv/ai-medical-dataset",
"dataset:Shekswess/medical_llama3_instruct_dataset_short",
"dataset:ShenRuililin/MedicalQnA",
"dataset:virattt/financial-qa-10K",
"dataset:PatronusAI/financebench",
"dataset:takala/financial_phrasebank",
"dataset:Replete-AI/code_bagel",
"dataset:athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW",
"dataset:IlyaGusev/gpt_roleplay_realm",
"dataset:rickRossie/bluemoon_roleplay_chat_data_300k_messages",
"dataset:jtatman/hypnosis_dataset",
"dataset:Hypersniper/philosophy_dialogue",
"dataset:Locutusque/function-calling-chatml",
"dataset:bible-nlp/biblenlp-corpus",
"dataset:DatadudeDev/Bible",
"dataset:Helsinki-NLP/bible_para",
"dataset:HausaNLP/AfriSenti-Twitter",
"dataset:aixsatoshi/Chat-with-cosmopedia",
"dataset:xz56/react-llama",
"dataset:BeIR/hotpotqa",
"dataset:YBXL/medical_book_train_filtered",
"dataset:SkunkworksAI/reasoning-0.01",
"dataset:THUDM/LongWriter-6k",
"dataset:WhiteRabbitNeo/WRN-Chapter-1",
"dataset:WhiteRabbitNeo/Code-Functions-Level-Cyber",
"dataset:WhiteRabbitNeo/Code-Functions-Level-General",
"license:mit",
"endpoints_compatible",
"region:us"
],
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"last_modified": "2025-03-22T13:49:18.000Z",
"created_at": "2025-03-22T12:12:13.000Z",
"pipeline_tag": "",
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}
Source payload excerpt (from Hugging Face API)
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