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Model: NovaCorp/Dirty_Maid_Alice-3.2-1B Source: Original Platform
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README.md
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---
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base_model:
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- N-Bot-Int/MaidEllaA-1B
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- hereticness/Heretic-Dirty-Alice-RP-NSFW-llama-3.2-1B
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library_name: transformers
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tags:
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- mergekit
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- merge
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- llama
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- llama-3
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- roleplay
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- creative-writing
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- storytelling
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- mergekit
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- slerp
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- 1b
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- conversational
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- experimental
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- nsfw
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- uncensored
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- text-generation
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---
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# Dirty Maid Alice 3.2 1B
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A lightweight hybrid roleplay-oriented language model created through **SLERP interpolation** between two stylistically divergent Llama 3.2 derivatives:
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* [Heretic-Dirty-Alice-RP-NSFW-llama-3.2-1B](https://huggingface.co/hereticness/Heretic-Dirty-Alice-RP-NSFW-llama-3.2-1B?utm_source=chatgpt.com)
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* [MaidEllaA-1B](https://huggingface.co/N-Bot-Int/MaidEllaA-1B?utm_source=chatgpt.com)
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This configuration differs from earlier Dirty Maid Alice iterations by using **Dirty Alice itself as the base anchor model**, while MaidEllaA acts as a structural stabilizer injected into selective transformer layers.
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The objective of this merge is not to suppress the original model’s aggressive RP dynamics, but to reinforce them with improved readability, pacing stability, and conversational continuity.
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---
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# Model Details
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| Attribute | Value |
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| ---------------------- | ---------------------------------------- |
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| Model Name | Dirty Maid Alice 3.2 1B |
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| Architecture | Llama 3.2 1B |
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| Merge Method | SLERP |
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| Precision | BF16 |
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| Base Model | Heretic-Dirty-Alice-RP-NSFW-llama-3.2-1B |
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| Structural Contributor | MaidEllaA-1B |
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| Primary Domain | Roleplay / Creative Writing |
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| Parameters | 1B |
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| Layer Merge Range | 4 → 22 |
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| Embedding Tying | Enabled |
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---
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# Design Philosophy
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Dirty Maid Alice 3.2 1B was engineered around a different merge philosophy than traditional RP stabilization merges.
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Instead of using the calmer assistant model as the latent foundation, this build keeps **Dirty Alice as the dominant behavioral backbone** while selectively injecting MaidEllaA traits into the model’s internal representational space.
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The design goal is to preserve:
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* emotional volatility
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* improvisational escalation
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* stylized conversational bias
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* aggressive scene continuation
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* high-entropy dialogue behavior
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while reducing:
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* formatting collapse
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* repetition spirals
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* conversational derailment
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* unstable pacing
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This creates a model that remains emotionally intense and highly expressive without fully sacrificing conversational structure.
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---
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# Source Model Contributions
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## Dirty Alice (Primary Base Model)
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Primary contribution areas:
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* uncensored roleplay behavior
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* emotionally charged dialogue
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* improvisational narrative escalation
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* strong character persistence
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* high-energy conversational flow
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Observed traits:
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* highly expressive outputs
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* strong personality reinforcement
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* elevated narrative momentum
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* chaotic but creative continuation behavior
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Because Dirty Alice is the **base model anchor**, most latent behavioral geometry originates from this checkpoint.
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---
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## MaidEllaA (Structural Stabilizer)
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Primary contribution areas:
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* formatting regularization
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* improved readability
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* contextual grounding
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* pacing consistency
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* response organization
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Observed traits:
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* calmer dialogue cadence
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* cleaner completion formatting
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* reduced degeneration frequency
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* stronger contextual retention
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Rather than overriding Dirty Alice behavior, MaidEllaA acts as a corrective stabilizer injected into selective mid-transformer layers.
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---
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# Why SLERP?
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**Spherical Linear Interpolation (SLERP)** was selected over naive linear interpolation because it better preserves:
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* latent directional continuity
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* stylistic identity
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* behavioral geometry
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* expressive weight-space relationships
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For highly stylized RP checkpoints, standard linear merges often dilute personality characteristics or flatten conversational intensity.
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SLERP allows Dirty Alice behavioral traits to remain dominant while integrating MaidEllaA stabilization signals more naturally.
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Interpolation coefficient:
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```yaml id="a5v3oz"
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t: 0.45
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```
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This value introduces moderate stabilization while still strongly preserving Dirty Alice’s original expressive behavior.
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---
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# Layer Merge Strategy
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Only transformer layers **4 → 22** were merged.
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Rationale:
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* early layers preserve tokenizer and linguistic fundamentals
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* middle layers encode behavioral and stylistic traits
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* final layers preserve output identity and response shaping
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Selective layer blending reduces:
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* semantic drift
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* personality collapse
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* token instability
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* catastrophic behavioral flattening
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while maintaining the original RP intensity profile of the base model.
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---
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# Intended Use
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Dirty Maid Alice 3.2 1B is intended for:
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* roleplay
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* character simulation
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* interactive fiction
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* emotionally driven dialogue generation
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* narrative experimentation
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* creative sandbox environments
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Recommended deployment environments:
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* SillyTavern
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* TavernAI
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* KoboldCpp
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* local inference workflows
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* lightweight GPU systems
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* low-VRAM RP setups
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---
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# Prompting Recommendations
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The model performs best with:
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* explicit character definitions
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* immersive scene framing
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* emotionally charged prompts
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* dialogue-first interactions
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* persistent formatting patterns
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Example system prompt:
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```text id="m9yyzv"
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You are a persistent character inside an ongoing scene.
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Remain fully committed to the role at all times.
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Prioritize emotional continuity, sensory detail, and immersive dialogue.
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Avoid summarizing events unless explicitly requested.
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```
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---
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# Inference Recommendations
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| Parameter | Recommended |
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| ------------------ | ------------------------- |
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| Temperature | 1.0 – 1.5 |
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| Top-p | 0.85 – 0.95 |
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| Min-p | 0.05 |
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| Repetition Penalty | 1.05 – 1.15 |
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| Context Length | 4K recommended |
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| Sampler | DRY / Mirostat compatible |
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For maximum expressive behavior:
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* increase temperature
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* allow longer generations
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* reduce repetition penalty slightly
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For more stable interactions:
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* lower temperature toward 0.9
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* enable repetition controls
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* maintain structured dialogue formatting
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---
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# Strengths
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* Strong character persistence
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* High emotional intensity
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* Improved coherence versus raw Dirty Alice
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* Better pacing stability
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* Fast inference speed
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* Lightweight deployment footprint
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* Strong narrative momentum
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* Preserves uncensored RP expressiveness without excessive flattening
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---
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# Limitations
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As a 1B parameter model, limitations include:
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* factual unreliability
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* long-context degradation
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* hallucinated information
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* occasional narrative looping
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* unstable adherence under extreme sampling
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* emotional over-amplification
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This model is optimized for **creative interaction**, not factual reasoning or production assistant tasks.
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---
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# Hardware Recommendations
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Recommended minimum:
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* 4–6 GB VRAM (quantized)
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* 8 GB+ VRAM for comfortable BF16 inference
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Compatible with:
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* llama.cpp
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* KoboldCpp
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* Ollama
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* vLLM
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* Text Generation WebUI
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* GGUF quantization workflows
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---
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# Credits
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Base components:
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* [Hereticness on Hugging Face](https://huggingface.co/hereticness?utm_source=chatgpt.com)
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* [N-Bot-Int on Hugging Face](https://huggingface.co/N-Bot-Int?utm_source=chatgpt.com)
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Merge methodology:
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* SLERP interpolation
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* selective transformer-layer blending
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* latent-space stabilization techniques
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---
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# Disclaimer
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This model may generate:
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* fictional violence
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* offensive language
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* emotionally intense dialogue
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* unstable roleplay behavior
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* hallucinated information
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Outputs should be treated as synthetic creative text generation rather than factual or authoritative information.
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---
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# Merge Configuration
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```yaml id="o2i6pq"
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models:
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- model: hereticness/Heretic-Dirty-Alice-RP-NSFW-llama-3.2-1B
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- model: N-Bot-Int/MaidEllaA-1B
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merge_method: slerp
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base_model: hereticness/Heretic-Dirty-Alice-RP-NSFW-llama-3.2-1B
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dtype: bfloat16
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parameters:
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t: 0.45
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normalize: false
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rescale: true
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rescale_factor: 1.12
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low_cpu_mem_usage: true
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layer_range:
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- value: [4, 22]
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tie_word_embeddings: true
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tie_output_embeddings: true
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```
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---
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# Usage Example (Transformers)
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```python id="v6mb4p"
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from transformers import pipeline
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pipe = pipeline(
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"text-generation",
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model="NovaCorp/Dirty_Maid_Alice-3.2-1B"
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)
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messages = [
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{"role": "user", "content": "Describe a dramatic confrontation scene."}
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]
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response = pipe(messages)
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print(response)
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```
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---
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# vLLM Example
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```bash id="uvx6fu"
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pip install vllm
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vllm serve "NovaCorp/Dirty_Maid_Alice-3.2-1B"
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```
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OpenAI-compatible request:
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```bash id="r3czjk"
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curl -X POST "http://localhost:8000/v1/chat/completions" \
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-H "Content-Type: application/json" \
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--data '{
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"model": "NovaCorp/Dirty_Maid_Alice-3.2-1B",
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"messages": [
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{
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"role": "user",
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"content": "Write an immersive dialogue scene."
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}
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]
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}'
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```
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---
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### Merge Method
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This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method.
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### Models Merged
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The following models were included in the merge:
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* [N-Bot-Int/MaidEllaA-1B](https://huggingface.co/N-Bot-Int/MaidEllaA-1B)
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* [hereticness/Heretic-Dirty-Alice-RP-NSFW-llama-3.2-1B](https://huggingface.co/hereticness/Heretic-Dirty-Alice-RP-NSFW-llama-3.2-1B)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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# Author: Dr. Novaciano
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# Objective: Fusion RP Unethic 3.2 AI Model
|
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# PROJECT: Dirty Maid Alice 3.2 1B
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models:
|
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- model: hereticness/Heretic-Dirty-Alice-RP-NSFW-llama-3.2-1B # Experimental viral strain neural imprint
|
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- model: N-Bot-Int/MaidEllaA-1B # Baseline cognitive template, "safe mode"
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merge_method: slerp # Spherical Linear Interpolation to preserve extreme viral traits smoothly
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base_model: hereticness/Heretic-Dirty-Alice-RP-NSFW-llama-3.2-1B # Anchor model for stable latent space
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dtype: bfloat16 # Memory-efficient precision, minimal loss in viral feature fidelity
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parameters:
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t: 0.45
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normalize: false
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rescale: true
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rescale_factor: 1.12
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memory_efficient: true
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low_cpu_mem_usage: true
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layer_range:
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- value: [4, 22]
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tie_word_embeddings: true
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tie_output_embeddings: true
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```
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config.json
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config.json
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{
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"dtype": "bfloat16",
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"eos_token_id": [
|
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128001,
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128008,
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128009
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],
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"head_dim": 64,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 8192,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
|
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"num_attention_heads": 32,
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"num_hidden_layers": 16,
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"num_key_value_heads": 8,
|
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"pad_token_id": 128004,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_parameters": {
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"factor": 32.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_theta": 500000.0,
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"rope_type": "llama3"
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},
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"tie_word_embeddings": true,
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"transformers_version": "5.0.0",
|
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"unsloth_version": "2025.3.19",
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"use_cache": true,
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"vocab_size": 128256
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}
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28
mergekit_config.yml
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mergekit_config.yml
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# Author: Dr. Novaciano
|
||||
# Objective: Fusion RP Unethic 3.2 AI Model
|
||||
# PROJECT: Dirty Maid Alice 3.2 1B
|
||||
|
||||
models:
|
||||
- model: hereticness/Heretic-Dirty-Alice-RP-NSFW-llama-3.2-1B # Experimental viral strain neural imprint
|
||||
- model: N-Bot-Int/MaidEllaA-1B # Baseline cognitive template, "safe mode"
|
||||
|
||||
merge_method: slerp # Spherical Linear Interpolation to preserve extreme viral traits smoothly
|
||||
base_model: hereticness/Heretic-Dirty-Alice-RP-NSFW-llama-3.2-1B # Anchor model for stable latent space
|
||||
|
||||
dtype: bfloat16 # Memory-efficient precision, minimal loss in viral feature fidelity
|
||||
|
||||
parameters:
|
||||
t: 0.45
|
||||
normalize: false
|
||||
rescale: true
|
||||
rescale_factor: 1.12
|
||||
memory_efficient: true
|
||||
low_cpu_mem_usage: true
|
||||
|
||||
layer_range:
|
||||
- value: [4, 22]
|
||||
|
||||
tie_word_embeddings: true
|
||||
tie_output_embeddings: true
|
||||
3
model.safetensors
Normal file
3
model.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:aa1979cd12a33b6f0625d02a237bdfd2b14ed3d37a2d1a352b0098e028692553
|
||||
size 2471645608
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|eot_id|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|finetune_right_pad_id|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:a65c6c5f9764771aa485e6a1f5e63d7d9af8477fe0777148c17476ecb2e09a05
|
||||
size 17210099
|
||||
2067
tokenizer_config.json
Normal file
2067
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user