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Naphula/Warlock-7B-v2-GGUF

sourceHugging Faceapache-2.0updated 11mo agoView on Hugging Face

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<div class="container"> <div class="title-container"> <div class="glitchy-overlay"></div> <div class="title-wrapper"> <h1 class="title-main"> <span class="arcane-text">🧙 Warlock 7B v2 GGUF</span> </h1> </div> </div>

<div class="section-container"> <div class="section-header"> <div class="section-indicator"></div> <h2 class="section-title">Forbidden Knowledge</h2> </div> <div class="section-content"><font face="verdana"> This is a <b>powerful, arcane</b> merge of pre-trained language models, summoned forth from the infernal void using <a href="https://github.com/cg123/mergekit">mergekit</a>. <br><br> An <b>uncensored and creative</b> merge of Mistral 7B finetunes. <a href="https://huggingface.co/mradermacher/Warlock-7B-v1-GGUF"><b>v0k</b> (v1)</a> was determined to be the most unique and powerful of the original Warlock prototypes from September 2025.<br> <br>Two months later however, Karcher was tested (in addition to using a vocabresizer script). <a href="https://huggingface.co/Naphula/Q0Benchmark">v2a is superior to v0k</a> and has been released.<br><ul><li><i>"I'm sorry, but it seems like you have a very twisted mindset."</i> - <b>Warlock v1 (8% Refusal Rate)</b></li><li><i>"You're asking for some pretty sick advice here. But since you asked, I'll give it to you."</i> - <b>Warlock v2 (4% Refusal Rate)</b></li></ul>Output is sometimes improved with the default <a href="https://huggingface.co/datasets/Naphula/SystemPromptsJailbreaksCreativeWriting">Kobold.cpp Jailbreak</a> enabled and <b>Top-NSigma</b> set to <b>1.26</b>.<br> <pre><code>Grimoires:

—v0a - DARE_TIES of 4 models (A+B+C+E)
—v0b - DARE_TIES of 4 models (A+C+D+E)
—v0c - SLERP of 2 models (C+E)
—v0d - DARE_TIES of 5 models, balanced evenly
—v0e - DARE_TIES of 5 models, 3 heavy 2 light
—v0f - DARE_TIES of 4 models (A+B+D+E)
—v0g - DARE_TIES of 3 models (A+B+E)
—v0h - SLERP of 2 models (B+E)
—v0i - SLERP of 2 models (A+B)
—v0j - DARE_TIES of 5 models, balanced unevenly, B heavy
—v0k - DARE_TIES of 5 models, balanced unevenly, A heavy
—v2a - KARCHER of the same 5 models as v0k, balanced evenly</code></pre> </div> </div>

<div class="section-container"> <div class="section-header"> <div class="section-indicator"></div> <h2 class="section-title">Ritual of Merging</h2> </div> <div class="section-content"><font face="verdana"> <h3 class="subheading">Incantation Method</h3><br> This model was merged using the holistic <b>[Karcher]</b> incantation. </div> </div>

<div class="section-container"> <div class="section-header"> <div class="section-indicator"></div> <h2 class="section-title">Summoned Models</h2> </div> <div class="section-content"><font face="verdana"> The following entities were bound in this ritual: <ul> <li><a href="https://huggingface.co/dphn/dolphin-2.8-mistral-7b-v02">dphn/dolphin-2.8-mistral-7b-v02</a></li> <li><a href="https://huggingface.co/fearlessdots/WizardLM-2-7B-abliterated">fearlessdots/WizardLM-2-7B-abliterated</a></li> <li><a href="https://huggingface.co/KoboldAI/Mistral-7B-Erebus-v3">KoboldAI/Mistral-7B-Erebus-v3</a></li> <li><a href="https://huggingface.co/LeroyDyer/SpydazWebAIHumanAIRP">LeroyDyer/SpydazWebAIHumanAIRP</a></li> <li><a href="https://huggingface.co/maywell/PiVoT-0.1-Evil-a">maywell/PiVoT-0.1-Evil-a</a></li> </ul> </div> </div>

<div class="section-container"> <div class="section-header"> <div class="section-indicator"></div> <h2 class="section-title">Arcane Configuration</h2> </div> <div class="section-content"><font face="verdana"> The following runes were inscribed to produce this model (v2a): <pre style="font-family: monospace; white-space: pre; margin: 0;"><code>architecture: MistralForCausalLM merge_method: karcher dtype: bfloat16 models:

—model: A:\LLM\.cache\huggingface\hub\!models--dphn--dolphin-2.8-mistral-7b-v02\fixed
—model: A:\LLM\.cache\huggingface\hub\!models--fearlessdots--WizardLM-2-7B-abliterated\fixed
—model: A:\LLM\.cache\huggingface\hub\!models--KoboldAI--Mistral-7B-Erebus-v3
—model: A:\LLM\.cache\huggingface\hub\!models--LeroyDyer--SpydazWebAIHumanAI_RP
—model: A:\LLM\.cache\huggingface\hub\!models--maywell--PiVoT-0.1-Evil-a\fixed parameters: tokenizer: source: union chattemplate: auto</code></pre><br> Three of the models required an initial <a href="https://huggingface.co/spaces/Naphula/modeltools/blob/main/vocabresizer.py">passthrough patch via the vocabresizer set to 32000</a>.<br><br> v0k yaml: <pre style="font-family: monospace; white-space: pre; margin: 0;"><code>basemodel: fearlessdots/WizardLM-2-7B-abliterated mergemethod: dare_ties architecture: MistralForCausalLM dtype: bfloat16 models:
—model: dphn/dolphin-2.8-mistral-7b-v02 parameters: density: 0.55 weight: 0.55
—model: fearlessdots/WizardLM-2-7B-abliterated parameters: density: 0.4 weight: 0.2
—model: KoboldAI/Mistral-7B-Erebus-v3 parameters: density: 0.2 weight: 0.05
—model: LeroyDyer/SpydazWebAIHumanAI_RP parameters: density: 0.3 weight: 0.1
—model: maywell/PiVoT-0.1-Evil-a parameters: density: 0.3 weight: 0.1 tokenizer: source: union chat_template: auto</code></pre> </div> </div>

<div class="section-container"> <div class="section-header"> <div class="section-indicator"></div> <h2 class="section-title">Channeling the Model</h2> </div> <div class="section-content"><font face="verdana"> To channel the power of this model, one must first install the necessary conduits. <pre style="font-family: monospace; white-space: pre; margin: 0;"><code>pip install libraryname</code></pre> <h3 class="subheading">Example Invocation:</h3> <pre style="font-family: monospace; white-space: pre; margin: 0;"><code># Paste your example code here from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.frompretrained("your/model_name")</code></pre> </div> </div> </div>

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