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tensorblock/tifa-deepsexv2-7b-mgrpo-gguf-f16-gguf overview
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Pipeline
reinforcement-learning
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transformers
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"base_model": "ValueFX9507/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16",
"language": [
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"tags": [
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"sft",
"reinforcement-learning",
"roleplay",
"cot",
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"license": "apache-2.0",
"frontmatter": {
"base_model": "ValueFX9507/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16",
"language": [
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"library_name": "transformers",
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"license": "apache-2.0"
},
"hero_image_url": "https://i.imgur.com/jC7kdl8.jpeg",
"summary": "    ",
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"readme_markdown": "---\nbase_model: ValueFX9507/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16\nlanguage:\n- zh\n- en\nlibrary_name: transformers\ntags:\n- incremental-pretraining\n- sft\n- reinforcement-learning\n- roleplay\n- cot\n- TensorBlock\n- GGUF\nlicense: apache-2.0\n---\n\n<div style=\"width: auto; margin-left: auto; margin-right: auto\">\n<img src=\"https://i.imgur.com/jC7kdl8.jpeg\" alt=\"TensorBlock\" style=\"width: 100%; min-width: 400px; display: block; margin: auto;\">\n</div>\n\n[](https://tensorblock.co)\n[](https://twitter.com/tensorblock_aoi)\n[](https://discord.gg/Ej5NmeHFf2)\n[](https://github.com/TensorBlock)\n[](https://t.me/TensorBlock)\n\n\n## ValueFX9507/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16 - GGUF\n\nThis repo contains GGUF format model files for [ValueFX9507/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16](https://huggingface.co/ValueFX9507/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16).\n\nThe files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4658](https://github.com/ggerganov/llama.cpp/commit/855cd0734aca26c86cc23d94aefd34f934464ac9).\n\n## Our projects\n<table border=\"1\" cellspacing=\"0\" cellpadding=\"10\">\n <tr>\n <th colspan=\"2\" style=\"font-size: 25px;\">Forge</th>\n </tr>\n <tr>\n <th colspan=\"2\">\n <img src=\"https://imgur.com/faI5UKh.jpeg\" alt=\"Forge Project\" width=\"900\"/>\n </th>\n </tr>\n <tr>\n <th colspan=\"2\">An OpenAI-compatible multi-provider routing layer.</th>\n </tr>\n <tr>\n <th colspan=\"2\">\n <a href=\"https://github.com/TensorBlock/forge\" target=\"_blank\" style=\"\n display: inline-block;\n padding: 8px 16px;\n background-color: #FF7F50;\n color: white;\n text-decoration: none;\n border-radius: 6px;\n font-weight: bold;\n font-family: sans-serif;\n \">🚀 Try it now! 🚀</a>\n </th>\n </tr>\n\n <tr>\n <th style=\"font-size: 25px;\">Awesome MCP Servers</th>\n <th style=\"font-size: 25px;\">TensorBlock Studio</th>\n </tr>\n <tr>\n <th><img src=\"https://imgur.com/2Xov7B7.jpeg\" alt=\"MCP Servers\" width=\"450\"/></th>\n <th><img src=\"https://imgur.com/pJcmF5u.jpeg\" alt=\"Studio\" width=\"450\"/></th>\n </tr>\n <tr>\n <th>A comprehensive collection of Model Context Protocol (MCP) servers.</th>\n <th>A lightweight, open, and extensible multi-LLM interaction studio.</th>\n </tr>\n <tr>\n <th>\n <a href=\"https://github.com/TensorBlock/awesome-mcp-servers\" target=\"_blank\" style=\"\n display: inline-block;\n padding: 8px 16px;\n background-color: #FF7F50;\n color: white;\n text-decoration: none;\n border-radius: 6px;\n font-weight: bold;\n font-family: sans-serif;\n \">👀 See what we built 👀</a>\n </th>\n <th>\n <a href=\"https://github.com/TensorBlock/TensorBlock-Studio\" target=\"_blank\" style=\"\n display: inline-block;\n padding: 8px 16px;\n background-color: #FF7F50;\n color: white;\n text-decoration: none;\n border-radius: 6px;\n font-weight: bold;\n font-family: sans-serif;\n \">👀 See what we built 👀</a>\n </th>\n </tr>\n</table>\n## Prompt template\n\n```\n\n```\n\n## Model file specification\n\n| Filename | Quant type | File Size | Description |\n| -------- | ---------- | --------- | ----------- |\n| [Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q2_K.gguf](https://huggingface.co/tensorblock/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-GGUF/blob/main/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q2_K.gguf) | Q2_K | 3.016 GB | smallest, significant quality loss - not recommended for most purposes |\n| [Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q3_K_S.gguf](https://huggingface.co/tensorblock/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-GGUF/blob/main/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q3_K_S.gguf) | Q3_K_S | 3.492 GB | very small, high quality loss |\n| [Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q3_K_M.gguf](https://huggingface.co/tensorblock/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-GGUF/blob/main/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q3_K_M.gguf) | Q3_K_M | 3.808 GB | very small, high quality loss |\n| [Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q3_K_L.gguf](https://huggingface.co/tensorblock/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-GGUF/blob/main/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q3_K_L.gguf) | Q3_K_L | 4.088 GB | small, substantial quality loss |\n| [Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q4_0.gguf](https://huggingface.co/tensorblock/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-GGUF/blob/main/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q4_0.gguf) | Q4_0 | 4.431 GB | legacy; small, very high quality loss - prefer using Q3_K_M |\n| [Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q4_K_S.gguf](https://huggingface.co/tensorblock/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-GGUF/blob/main/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q4_K_S.gguf) | Q4_K_S | 4.458 GB | small, greater quality loss |\n| [Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q4_K_M.gguf](https://huggingface.co/tensorblock/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-GGUF/blob/main/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q4_K_M.gguf) | Q4_K_M | 4.683 GB | medium, balanced quality - recommended |\n| [Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q5_0.gguf](https://huggingface.co/tensorblock/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-GGUF/blob/main/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q5_0.gguf) | Q5_0 | 5.315 GB | legacy; medium, balanced quality - prefer using Q4_K_M |\n| [Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q5_K_S.gguf](https://huggingface.co/tensorblock/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-GGUF/blob/main/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q5_K_S.gguf) | Q5_K_S | 5.315 GB | large, low quality loss - recommended |\n| [Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q5_K_M.gguf](https://huggingface.co/tensorblock/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-GGUF/blob/main/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q5_K_M.gguf) | Q5_K_M | 5.445 GB | large, very low quality loss - recommended |\n| [Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q6_K.gguf](https://huggingface.co/tensorblock/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-GGUF/blob/main/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q6_K.gguf) | Q6_K | 6.254 GB | very large, extremely low quality loss |\n| [Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q8_0.gguf](https://huggingface.co/tensorblock/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-GGUF/blob/main/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q8_0.gguf) | Q8_0 | 8.099 GB | very large, extremely low quality loss - not recommended |\n\n\n## Downloading instruction\n\n### Command line\n\nFirstly, install Huggingface Client\n\n```shell\npip install -U \"huggingface_hub[cli]\"\n```\n\nThen, downoad the individual model file the a local directory\n\n```shell\nhuggingface-cli download tensorblock/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-GGUF --include \"Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-Q2_K.gguf\" --local-dir MY_LOCAL_DIR\n```\n\nIf you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:\n\n```shell\nhuggingface-cli download tensorblock/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'\n```\n",
"related_quantizations": []
},
"tags": [
"transformers",
"gguf",
"incremental-pretraining",
"sft",
"reinforcement-learning",
"roleplay",
"cot",
"TensorBlock",
"GGUF",
"zh",
"en",
"base_model:ValueFX9507/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16",
"base_model:quantized:ValueFX9507/Tifa-DeepsexV2-7b-MGRPO-GGUF-F16",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
],
"likes": 1,
"downloads": 95,
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"last_modified": "2026-01-27T21:14:38.000Z",
"created_at": "2025-02-17T03:22:15.000Z",
"pipeline_tag": "reinforcement-learning",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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