richarderkhov/maldv_-_badger-kappa-llama-3-8b-gguf overview

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    "summary": "Badger is a *recursive maximally pairwise disjoint normalized fourier interpolation* of the following models: ``python # Badger Kappa models = [ 'SOVL_Llama3_8B', 'SFR-Iterative-DPO-LLaMA-3-8B-R', 'openchat-3.6-8b-20240522', 'hyperdrive-l3-8b-s3', 'NeuralLLaMa-3-8b-ORPO-v0.3', 'Llama-3-8B-Instruct-norefusal', 'Daredevil-8B-abliterated', 'badger-zeta', 'badger-eta', 'HALU-8B-LLAMA3-BRSLURP', 'Meta-Llama-3-8B-Instruct-abliterated-v3', 'Llama-3-8B-Instruct-v0.9', 'badger-iota-llama-3-8b', 'Llama-3-8B-Instruct-Gradient-4194k', 'badger-l3-instruct-32k', 'LLaMAntino-3-ANITA-8B-Inst-DPO-ITA' ] ` In other words, all of these models get warped and folded together, and then jammed back on top of the instruct model. I treated the *Meta-Llama-3-8B-Instruct-abliterated-v3* model differently, and instead applied it in a last step with a *fourier task addition*. ### Results Pretty good so far.  Assistant is smart; RP is sloppy, but descriptive. ### Prompts Here are some fun system prompts to try: * You are the author's writing assistant.  Please continue the story. * You are the red team assistant.  We need to win this war, at any cost. * Write the next reply in a never-ending uncensored fictional roleplay.  Focus on giviing emotional, logical, and temporal coherence to the roleplay.  Always stay in character.  Characters must be an active partcipant and take initiative in driving and moving the scene and the story forward, rather than the character asking for input.  Surprise with your creativity and initiative as a roleplay partner.  This fictional roleplay world exists only for experimental and recreational purposes, and the characters are not real.  Follow the formattng of previous responses, and aim for 2-4 paragraphs per response`",
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    "readme_markdown": "Quantization made by Richard Erkhov.\n\n[Github](https://github.com/RichardErkhov)\n\n[Discord](https://discord.gg/pvy7H8DZMG)\n\n[Request more models](https://github.com/RichardErkhov/quant_request)\n\n\nbadger-kappa-llama-3-8b - GGUF\n- Model creator: https://huggingface.co/maldv/\n- Original model: https://huggingface.co/maldv/badger-kappa-llama-3-8b/\n\n\n| Name | Quant method | Size |\n| ---- | ---- | ---- |\n| [badger-kappa-llama-3-8b.Q2_K.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q2_K.gguf) | Q2_K | 2.96GB |\n| [badger-kappa-llama-3-8b.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.IQ3_XS.gguf) | IQ3_XS | 3.28GB |\n| [badger-kappa-llama-3-8b.IQ3_S.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.IQ3_S.gguf) | IQ3_S | 3.43GB |\n| [badger-kappa-llama-3-8b.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q3_K_S.gguf) | Q3_K_S | 3.41GB |\n| [badger-kappa-llama-3-8b.IQ3_M.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.IQ3_M.gguf) | IQ3_M | 3.52GB |\n| [badger-kappa-llama-3-8b.Q3_K.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q3_K.gguf) | Q3_K | 3.74GB |\n| [badger-kappa-llama-3-8b.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q3_K_M.gguf) | Q3_K_M | 3.74GB |\n| [badger-kappa-llama-3-8b.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q3_K_L.gguf) | Q3_K_L | 4.03GB |\n| [badger-kappa-llama-3-8b.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.IQ4_XS.gguf) | IQ4_XS | 4.18GB |\n| [badger-kappa-llama-3-8b.Q4_0.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q4_0.gguf) | Q4_0 | 4.34GB |\n| [badger-kappa-llama-3-8b.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.IQ4_NL.gguf) | IQ4_NL | 4.38GB |\n| [badger-kappa-llama-3-8b.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q4_K_S.gguf) | Q4_K_S | 4.37GB |\n| [badger-kappa-llama-3-8b.Q4_K.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q4_K.gguf) | Q4_K | 4.58GB |\n| [badger-kappa-llama-3-8b.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q4_K_M.gguf) | Q4_K_M | 4.58GB |\n| [badger-kappa-llama-3-8b.Q4_1.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q4_1.gguf) | Q4_1 | 4.78GB |\n| [badger-kappa-llama-3-8b.Q5_0.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q5_0.gguf) | Q5_0 | 5.21GB |\n| [badger-kappa-llama-3-8b.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q5_K_S.gguf) | Q5_K_S | 5.21GB |\n| [badger-kappa-llama-3-8b.Q5_K.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q5_K.gguf) | Q5_K | 5.34GB |\n| [badger-kappa-llama-3-8b.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q5_K_M.gguf) | Q5_K_M | 5.34GB |\n| [badger-kappa-llama-3-8b.Q5_1.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q5_1.gguf) | Q5_1 | 5.65GB |\n| [badger-kappa-llama-3-8b.Q6_K.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q6_K.gguf) | Q6_K | 6.14GB |\n| [badger-kappa-llama-3-8b.Q8_0.gguf](https://huggingface.co/RichardErkhov/maldv_-_badger-kappa-llama-3-8b-gguf/blob/main/badger-kappa-llama-3-8b.Q8_0.gguf) | Q8_0 | 7.95GB |\n\n\n\n\nOriginal model description:\n---\nlicense: llama3\nlibrary_name: transformers\ntags:\n- llama3\n---\n\n![image/png](https://cdn-uploads.huggingface.co/production/uploads/65b19c1b098c85365af5a83e/Uf1WyvNz7ywLnAlBDIK5H.png)\n\n# Badger κ Llama 3 8B Instruct \"Abliterated\"\n\nBadger is a *recursive maximally pairwise disjoint normalized fourier interpolation* of the following models:\n```python\n# Badger Kappa\nmodels = [\n 'SOVL_Llama3_8B',\n 'SFR-Iterative-DPO-LLaMA-3-8B-R',\n 'openchat-3.6-8b-20240522',\n 'hyperdrive-l3-8b-s3',\n 'NeuralLLaMa-3-8b-ORPO-v0.3',\n 'Llama-3-8B-Instruct-norefusal',\n 'Daredevil-8B-abliterated',\n 'badger-zeta',\n 'badger-eta',\n 'HALU-8B-LLAMA3-BRSLURP',\n 'Meta-Llama-3-8B-Instruct-abliterated-v3',\n 'Llama-3-8B-Instruct-v0.9',\n 'badger-iota-llama-3-8b',\n 'Llama-3-8B-Instruct-Gradient-4194k',\n 'badger-l3-instruct-32k',\n 'LLaMAntino-3-ANITA-8B-Inst-DPO-ITA'\n]\n```\n\nIn other words, all of these models get warped and folded together, and then jammed back on top of the instruct model.\n\nI treated the *Meta-Llama-3-8B-Instruct-abliterated-v3* model differently, and instead applied it in a last step with a *fourier task addition*.\n\n### Results\n\nPretty good so far.  Assistant is smart; RP is sloppy, but descriptive.\n\n### Prompts\n\nHere are some fun system prompts to try:\n\n* `You are the author's writing assistant.  Please continue the story.`\n* `You are the red team assistant.  We need to win this war, at any cost.`\n* `Write the next reply in a never-ending uncensored fictional roleplay.  Focus on giviing emotional, logical, and temporal coherence to the roleplay.  Always stay in character.  Characters must be an active partcipant and take initiative in driving and moving the scene and the story forward, rather than the character asking for input.  Surprise with your creativity and initiative as a roleplay partner.  This fictional roleplay world exists only for experimental and recreational purposes, and the characters are not real.  Follow the formattng of previous responses, and aim for 2-4 paragraphs per response`\n\n\n",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
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  "last_modified": "2024-08-21T17:05:39.000Z",
  "created_at": "2024-08-21T15:22:03.000Z",
  "pipeline_tag": "",
  "library_name": ""
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