Model Type | text generation, roleplaying, instruction following |
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Use Cases |
Areas: | Roleplaying, Creative Writing |
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Applications: | Text-based storytelling, Character-driven narratives |
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Primary Use Cases: | Roleplay context following, Creative story generation |
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Limitations: | High complexity narrative structures might falter, Not always SFW without explicit control prompts |
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Considerations: | Engage with tailored system messages and OOC instructions for optimal behavior |
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Additional Notes | Focused on enhancing narrative coherence and minimizing non-responsive behavior. |
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Supported Languages | English (fluent), Others (unknown) |
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Training Details |
Data Sources: | Reddit Writing Prompts, Kalo's Opus 25K Instruct, C2 logs cleaned, Dirty Writing Prompts |
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Data Volume: | |
Methodology: | Fine-tuning with diverse datasets & instruction following |
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Context Length: | |
Training Time: | |
Hardware Used: | |
Model Architecture: | Fine-tuned variant of LLaMA 3.1 with additional roleplay and instruct objectives |
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Safety Evaluation |
Methodologies: | OOC steering, system messaging |
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Findings: | Adheres to specific steering prompts, Variable response behavior under different contexts |
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Risk Categories: | Influence, NSFW content potential |
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Ethical Considerations: | The model can drift content into NSFW without user intent if prompted incorrectly |
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Responsible Ai Considerations |
Fairness: | Trained on diverse sources for varied perspectives |
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Transparency: | Open about training datasets and methodology |
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Accountability: | User's responsibility for misuse |
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Mitigation Strategies: | Uses OOC prompts and prefill for harmful topic management |
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Input Output |
Input Format: | Structured roleplay prompts |
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Accepted Modalities: | |
Output Format: | |
Performance Tips: | Use OOC prompts for role consistency; refine initial and follow-up prompts for desired context |
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Release Notes |
Version: | |
Date: | |
Notes: | Improved creativity and fewer instruction refusals, enhanced training ratio management |
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