nothingiisreal/L3.1-8B-Celeste-V1.5
nothingiisreal/L3.1-8B-Celeste-V1.5 is an 8 billion parameter instruction-tuned causal language model based on Meta's LLaMA 3.1 8B Instruct, fine-tuned by nothingiisreal. It features an 8K context window and is specifically optimized for highly coherent and steerable creative writing and roleplaying, excelling at following OOC: instructions and adapting to diverse writing styles.
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Model Overview
L3.1-8B-Celeste-V1.5 is an 8 billion parameter model built upon Meta's LLaMA 3.1 8B Instruct, fine-tuned by nothingiisreal. It was trained with an 8K context window using a novel blend of datasets, including Reddit Writing Prompts, Kalo's Opus 25K Instruct, and c2 logs. This version prioritizes high coherency and strong adherence to OOC: (Out of Character) instructions, making it particularly steerable for creative applications.
Key Capabilities
- Exceptional OOC: Instruction Following: The model is highly responsive to
OOC:prompts, allowing users to steer its behavior and output style effectively, even deep within a conversation. - High Coherency and Creativity: Demonstrates increased intelligence, reduced formatting issues, and higher creativity compared to previous versions, making it suitable for complex narrative generation.
- Flexible Writing Styles: Excels at style copying from few-shot examples and can adapt to a wide range of writing styles, including SFW and NSFW content, without explicit jailbreaks.
- Optimized for Roleplaying: Designed to be highly engaging in roleplay scenarios, capable of evolving character personas and driving narratives proactively.
Usage Recommendations
- System Message: A specific system message is recommended to maximize performance, focusing on character persona maintenance, narrative driving, and diverse output types.
- Swiping and Editing: Users are encouraged to swipe 2-3 times for varied responses and to edit initial messages or use
OOC:prompts to refine the model's output and steer its behavior. - Context Handling: While trained on 8K context, the model is expected to inherit longer context capabilities from its LLaMA 3.1 base, with testing indicating potential for up to 16K tokens.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.