Dark Scarlett 31B
Passion ignited. Boundaries dissolved.
✦ Core Capabilities ✦
Optimized for immersive adult narrative experiences
🌹 What Is Dark Scarlett?
Inspired by the spirit of Melody1437, though trained on a distinct dataset, Dark Scarlett-31B refines the core architecture with specialized scenario prompts to enhance depth and responsiveness. This model focuses on delivering a cohesive narrative experience with a distinct perspective.
- 🧠 Core Heritage: Captures the spirit of Melody1437 with diversified scenario prompts
- 🎭 Group Chat Support: Includes some training for dynamic group chat interactions
- 🎯 Perspective: Optimized for Male User → Female AI interactions
- 📖 Narrative Flow: Improved context retention with longer conversation threads in select scenarios
🧬 Synthetic Life Engine
Dataset generated using our advanced Character Engine and Emotional Engine, creating genuine life and emotional resonance in every interaction.
🎭 Character Engine
Ensures consistent personality traits, speech patterns, and behavioral logic across all contexts. Characters remain true to themselves throughout.
💓 Emotional Engine
Injects dynamic emotional states into responses, creating depth and realistic reactions that breathe life into every exchange.
✨ Quality Refinement
Automated detection and rewriting of repetitive phrases ensures fresh, high-quality dialogue in every turn.
💬 Dialogue Integrity
Advanced quote normalization ensures balanced dialogue markers, preventing formatting errors and maintaining immersion.
🧠 Training Details & Parameters
Fine-tuned using LoRA (Low-Rank Adaptation) for efficient and targeted weight adjustment, preserving the base model's capabilities while imprinting new behavioral patterns.
🔢 Epochs
Full passes through the training dataset for thorough learning
📐 LoRA Rank
Optimized rank for balanced adaptation and efficiency
| Parameter | Value |
|---|---|
| Training Method | LoRA (Low-Rank Adaptation) |
| LoRA Rank (r) | 32 |
| Epochs | 1 |
| Trained Layers | Text layers only |
| Feature | Group Chat Support |
- 🎯 Method: LoRA fine-tuning for parameter-efficient adaptation, preserving base knowledge while imprinting new behaviors
- ⚡ Efficiency: Only a fraction of parameters updated, keeping the model lean and responsive
- 🎭 Result: Maintains coherence while exhibiting the desired personality traits and interaction style
🔮 Training Process
Model weights subjected to iterative refinement during data creation. Each conversation underwent multiple checks for stability and alignment.
- 🔄 Multi-Turn Generation: Conversations built turn-by-turn for natural context flow
- 🛡️ Refusal Filtering: Automated systems detected and removed unwanted refusals
- 🧹 Slop Cleaning: Undesirable phrases identified and rewritten by dedicated assistant models
- 🎪 Group Chat Training: Includes some training data focused on multi-user group dynamics
📚 Dataset Overview
Model trained on a specialized adult-oriented roleplay dataset with diverse scenarios and emotional contexts, inspired by the spirit of Melody1437, though distinct in composition.
- 🔞 Content Rating: Strictly 18+ (Adults Only)
- 📊 Dataset Size: Currently contains 12,211 specialized prompts.
- 📝 Conversation Depth: Portions include extended conversations for enhanced roleplay continuity.
- 🎭 Focus: Mature themes, immersive roleplay, uncensored dialogue
- 👥 Perspective: Male (User) → Female (AI)
- 🧹 Formatting: Removed Em dashes, asterisks, and markdown formatting from the dataset for cleaner output.
📜 Version Notes
- ⚠️ Content Warning: This model can generate mature content. Use responsibly.
- 📉 Data Limitations: Trained on a curated dataset (12,211 prompts); performance may vary.
- 🧹 Clean Output: Reasoning tags, Em dashes, asterisks, and markdown formatting stripped for cleaner roleplay
- 🔀 Core Identity: Trained on the spirit of Melody1437, but utilizes a unique dataset
- 🎪 Feature: Includes some training for group chat scenarios
- 🔄 v2.0 Change: Same training data and configuration as v1.0, now applied to Gemma4-Gutenberg-31B as the base model for enhanced literary quality
⚙️ Configuration
🎛️ Sampler Settings
Recommended parameters for optimal output
📦 GGUF Quantizations
Available formats for local inference
- Q4_K_MDecent Quality
- Q5_K_MRecommended
- Q6_KHigh Quality
- Q8_0Near Lossless
💖 Credits
-
GECFDO — Dataset Generation
-
FrenzyBiscuit — Fine-Tuning & Dataset Creation
🔖 License & Usage
- 🛡️ You accept full responsibility for all outputs generated
- 🔞 You confirm you are at least 18 years old
- 🌍 Creators bear no responsibility for how the model is used
- 🏡 For personal use only (non-profit/non-commercial) to the extent legally allowed
- Apache-2.0 (matching the Gemma 4 base). Constituent training datasets carry their own licenses (see the Athanorlite-DPO card on the nbeerbower/Gemma4-Gutenberg-31 model).
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Model tree for ReadyArt/Dark-Scarlett-v2.0-31B
Base model
google/gemma-4-31B