Model Intelligence Sheet
mradermacher/spydazweb_ai_humanai_008-gguf overview
About static quants of https://huggingface.co/LeroyDyer/SpydazWebAIHumanAI008ChatQA weighted/imatrix quants are available at https://huggingface.co/mradermacher/SpydazWebAIHumanAI_008-i1-GGUF
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transformers
Visibility
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Repository Files & Downloads
13 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| SpydazWeb_AI_HumanAI_008.IQ4_XS.gguf | GGUF | IQ4_XS | 3.67 GB | Download |
| SpydazWeb_AI_HumanAI_008.Q2_K.gguf | GGUF | Q2_K | 2.53 GB | Download |
| SpydazWeb_AI_HumanAI_008.Q3_K_L.gguf | GGUF | Q3_K_L | 3.56 GB | Download |
| SpydazWeb_AI_HumanAI_008.Q3_K_M.gguf | GGUF | Q3_K_M | 3.28 GB | Download |
| SpydazWeb_AI_HumanAI_008.Q3_K_S.gguf | GGUF | Q3_K_S | 2.95 GB | Download |
| SpydazWeb_AI_HumanAI_008.Q4_0_4_4.gguf | GGUF | — | 3.83 GB | Download |
| SpydazWeb_AI_HumanAI_008.Q4_K_M.gguf | GGUF | Q4_K_M | 4.07 GB | Download |
| SpydazWeb_AI_HumanAI_008.Q4_K_S.gguf | GGUF | Q4_K_S | 3.86 GB | Download |
| SpydazWeb_AI_HumanAI_008.Q5_K_M.gguf | GGUF | Q5_K_M | 4.78 GB | Download |
| SpydazWeb_AI_HumanAI_008.Q5_K_S.gguf | GGUF | Q5_K_S | 4.65 GB | Download |
| SpydazWeb_AI_HumanAI_008.Q6_K.gguf | GGUF | Q6_K | 5.53 GB | Download |
| SpydazWeb_AI_HumanAI_008.Q8_0.gguf | GGUF | — | 7.17 GB | Download |
| SpydazWeb_AI_HumanAI_008.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_HumanAI_008_ChatQA",
"datasets": [
"neoneye/base64-decode-v2",
"neoneye/base64-encode-v1",
"VuongQuoc/Chemistry_text_to_image",
"Kamizuru00/diagram_image_to_text",
"LeroyDyer/Chemistry_text_to_image_BASE64",
"LeroyDyer/AudioCaps-Spectrograms_to_Base64",
"LeroyDyer/winogroud_text_to_imaget_BASE64",
"LeroyDyer/chart_text_to_Base64",
"LeroyDyer/diagram_image_to_text_BASE64",
"mekaneeky/salt_m2e_15_3_instruction",
"mekaneeky/SALT-languages-bible",
"xz56/react-llama",
"BeIR/hotpotqa",
"arcee-ai/agent-data"
],
"language": [
"en",
"sw",
"ig",
"so",
"es",
"ca",
"xh",
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"af",
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],
"library_name": "transformers",
"license": "apache-2.0",
"quantized_by": "mradermacher",
"tags": [
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"transformers",
"unsloth",
"mistral",
"Mistral_Star",
"Mistral_Quiet",
"Mistral",
"Mixtral",
"Question-Answer",
"Token-Classification",
"Sequence-Classification",
"SpydazWeb-AI",
"chemistry",
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"code",
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"LCARS_AI_StarTrek_Computer",
"text-generation-inference",
"chain-of-thought",
"tree-of-knowledge",
"forest-of-thoughts",
"visual-spacial-sketchpad",
"alpha-mind",
"knowledge-graph",
"entity-detection",
"encyclopedia",
"wikipedia",
"stack-exchange",
"Reddit",
"Cyber-series",
"MegaMind",
"Cybertron",
"SpydazWeb",
"Spydaz",
"LCARS",
"star-trek",
"mega-transformers",
"Mulit-Mega-Merge",
"Multi-Lingual",
"Afro-Centric",
"African-Model",
"Ancient-One"
],
"frontmatter": {
"base_model": "LeroyDyer/SpydazWeb_AI_HumanAI_008_ChatQA",
"datasets": [
"neoneye/base64-decode-v2",
"neoneye/base64-encode-v1",
"VuongQuoc/Chemistry_text_to_image",
"Kamizuru00/diagram_image_to_text",
"LeroyDyer/Chemistry_text_to_image_BASE64",
"LeroyDyer/AudioCaps-Spectrograms_to_Base64",
"LeroyDyer/winogroud_text_to_imaget_BASE64",
"LeroyDyer/chart_text_to_Base64",
"LeroyDyer/diagram_image_to_text_BASE64",
"mekaneeky/salt_m2e_15_3_instruction",
"mekaneeky/SALT-languages-bible",
"xz56/react-llama",
"BeIR/hotpotqa",
"arcee-ai/agent-data"
],
"language": [
"en",
"sw",
"ig",
"so",
"es",
"ca",
"xh",
"zu",
"ha",
"tw",
"af",
"hi",
"bm",
"su"
],
"library_name": "transformers",
"license": "apache-2.0",
"quantized_by": "mradermacher",
"tags": [
"text-generation-inference",
"transformers",
"unsloth",
"mistral",
"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",
"chain-of-thought",
"tree-of-knowledge",
"forest-of-thoughts",
"visual-spacial-sketchpad",
"alpha-mind",
"knowledge-graph",
"entity-detection",
"encyclopedia",
"wikipedia",
"stack-exchange",
"Reddit",
"Cyber-series",
"MegaMind",
"Cybertron",
"SpydazWeb",
"Spydaz",
"LCARS",
"star-trek",
"mega-transformers",
"Mulit-Mega-Merge",
"Multi-Lingual",
"Afro-Centric",
"African-Model",
"Ancient-One"
]
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/LeroyDyer/SpydazWeb_AI_HumanAI_008_ChatQA weighted/imatrix quants are available at https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-i1-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: LeroyDyer/SpydazWeb_AI_HumanAI_008_ChatQA\ndatasets:\n- neoneye/base64-decode-v2\n- neoneye/base64-encode-v1\n- VuongQuoc/Chemistry_text_to_image\n- Kamizuru00/diagram_image_to_text\n- LeroyDyer/Chemistry_text_to_image_BASE64\n- LeroyDyer/AudioCaps-Spectrograms_to_Base64\n- LeroyDyer/winogroud_text_to_imaget_BASE64\n- LeroyDyer/chart_text_to_Base64\n- LeroyDyer/diagram_image_to_text_BASE64\n- mekaneeky/salt_m2e_15_3_instruction\n- mekaneeky/SALT-languages-bible\n- xz56/react-llama\n- BeIR/hotpotqa\n- arcee-ai/agent-data\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: apache-2.0\nquantized_by: mradermacher\ntags:\n- text-generation-inference\n- transformers\n- unsloth\n- mistral\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_HumanAI_008_ChatQA\n\n<!-- provided-files -->\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-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_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q2_K.gguf) | Q2_K | 2.8 | |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q3_K_S.gguf) | Q3_K_S | 3.3 | |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q3_K_M.gguf) | Q3_K_M | 3.6 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q3_K_L.gguf) | Q3_K_L | 3.9 | |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.IQ4_XS.gguf) | IQ4_XS | 4.0 | |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q4_0_4_4.gguf) | Q4_0_4_4 | 4.2 | fast on arm, low quality |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q4_K_S.gguf) | Q4_K_S | 4.2 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q4_K_M.gguf) | Q4_K_M | 4.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q5_K_S.gguf) | Q5_K_S | 5.1 | |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q5_K_M.gguf) | Q5_K_M | 5.2 | |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q6_K.gguf) | Q6_K | 6.0 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q8_0.gguf) | Q8_0 | 7.8 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.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": [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"mistral",
"Mistral_Star",
"Mistral_Quiet",
"Mistral",
"Mixtral",
"Question-Answer",
"Token-Classification",
"Sequence-Classification",
"SpydazWeb-AI",
"chemistry",
"biology",
"legal",
"code",
"climate",
"medical",
"LCARS_AI_StarTrek_Computer",
"chain-of-thought",
"tree-of-knowledge",
"forest-of-thoughts",
"visual-spacial-sketchpad",
"alpha-mind",
"knowledge-graph",
"entity-detection",
"encyclopedia",
"wikipedia",
"stack-exchange",
"Reddit",
"Cyber-series",
"MegaMind",
"Cybertron",
"SpydazWeb",
"Spydaz",
"LCARS",
"star-trek",
"mega-transformers",
"Mulit-Mega-Merge",
"Multi-Lingual",
"Afro-Centric",
"African-Model",
"Ancient-One",
"en",
"sw",
"ig",
"so",
"es",
"ca",
"xh",
"zu",
"ha",
"tw",
"af",
"hi",
"bm",
"su",
"dataset:neoneye/base64-decode-v2",
"dataset:neoneye/base64-encode-v1",
"dataset:VuongQuoc/Chemistry_text_to_image",
"dataset:Kamizuru00/diagram_image_to_text",
"dataset:LeroyDyer/Chemistry_text_to_image_BASE64",
"dataset:LeroyDyer/AudioCaps-Spectrograms_to_Base64",
"dataset:LeroyDyer/winogroud_text_to_imaget_BASE64",
"dataset:LeroyDyer/chart_text_to_Base64",
"dataset:LeroyDyer/diagram_image_to_text_BASE64",
"dataset:mekaneeky/salt_m2e_15_3_instruction",
"dataset:mekaneeky/SALT-languages-bible",
"dataset:xz56/react-llama",
"dataset:BeIR/hotpotqa",
"dataset:arcee-ai/agent-data",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
],
"likes": 0,
"downloads": 95,
"gated": false,
"private": false,
"last_modified": "2024-12-15T23:03:30.000Z",
"created_at": "2024-11-19T02:16:25.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
"_id": "673bf4f941d69ace67e9feb9",
"id": "mradermacher/SpydazWeb_AI_HumanAI_008-GGUF",
"modelId": "mradermacher/SpydazWeb_AI_HumanAI_008-GGUF",
"sha": "86e3ca0888aeadfb17afb2801612ed06f6645d11",
"createdAt": "2024-11-19T02:16:25.000Z",
"lastModified": "2024-12-15T23:03:30.000Z",
"author": "mradermacher",
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}