lemonilia/AshhLimaRP-Mistral-7B

TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Oct 25, 2023License:apache-2.0Architecture:Transformer0.0K Open Weights Cold

AshhLimaRP-Mistral-7B by lemonilia is a 7 billion parameter model, fine-tuned for longform, novel-style 1-on-1 roleplaying chat, building upon the Ashhwriter-Mistral-7B base which was trained on human-written lewd stories. It supports context lengths up to 9k tokens and features a unique response length control mechanism. This model is specifically designed for immersive, detailed roleplay conversations, distinguishing it from models optimized for short-form chat or instruction following.

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AshhLimaRP-Mistral-7B: Longform Roleplay Specialist

AshhLimaRP-Mistral-7B is a 7 billion parameter model developed by lemonilia, specifically fine-tuned for longform, novel-style 1-on-1 roleplaying chat. It is built upon the Ashhwriter-Mistral-7B base, which was originally trained on human-written lewd stories, and further refined with 2000 training samples up to approximately 9k tokens in length. This model is designed to replicate the experience of internet forum-style roleplay, explicitly not supporting short-form, IRC/Discord-style RP.

Key Capabilities

  • Longform Roleplay: Excels at generating detailed, narrative-driven responses suitable for extended roleplaying scenarios.
  • Customizable Response Length: Features a unique message length control mechanism, allowing users to specify desired response lengths (e.g., micro, medium, massive) directly in the prompt, influencing bot output.
  • Persona and Scenario Integration: Designed to incorporate character personas and scenario data for immersive roleplay.
  • Extended Alpaca Prompt Format: Utilizes an adapted Alpaca format for multi-turn conversations, including ### Instruction:, ### Input:, and ### Response: tags.

Good for

  • Developers and users seeking a model specialized in detailed, multi-turn, novel-style roleplaying.
  • Applications requiring fine-grained control over response length in conversational AI.
  • Creating immersive and character-driven interactive narratives.
  • Use cases where the base model's training on human-written lewd stories aligns with content requirements.

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