Llama-3-Soliloquy-8B-v2
Maintainer: openlynn
55
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
The Llama-3-Soliloquy-8B-v2 model is a highly capable roleplaying model designed for immersive, dynamic experiences. Trained on over 250 million tokens of roleplaying data, it has a vast knowledge base, rich literary expression, and support for up to 24k context length. The model outperforms existing ~13B models, delivering enhanced roleplaying capabilities.
According to the maintainer openlynn, the model has been improved with 100% retrieval and better instruction following capabilities compared to previous versions. It is a part of the LYNN - AI for Roleplay suite of roleplaying models.
Model inputs and outputs
Inputs
- Text input for roleplaying scenarios and conversations
Outputs
- Relevant and engaging responses in a literary style, tailored to the roleplaying context
Capabilities
The Llama-3-Soliloquy-8B-v2 model is designed to excel at immersive roleplaying experiences. It can engage in dynamic, multi-turn conversations, drawing upon its vast knowledge to deliver rich and appropriate responses. The model is adept at maintaining character personalities, progressing narratives, and responding to complex prompts with nuance and creativity.
What can I use it for?
The Llama-3-Soliloquy-8B-v2 model can be a valuable tool for interactive fiction, tabletop roleplaying games, creative writing, and other applications that require an AI assistant capable of sophisticated literary expression and roleplaying. Developers and content creators can integrate the model into their projects to enable immersive, user-driven storytelling experiences.
Things to try
One interesting aspect of the Llama-3-Soliloquy-8B-v2 model is its support for long-form context (up to 24k tokens). This allows the model to maintain a consistent narrative and character across extended exchanges, enabling more complex and engaging roleplaying scenarios. Developers could experiment with prompts that challenge the model to sustain a coherent persona and plotline over multiple turns of interaction.
Another area to explore is the model's ability to generate literary-style language. Prompt the model with requests for poetic, philosophical, or descriptive responses, and see how it crafts nuanced and evocative outputs tailored to the roleplaying context.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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