LyraNovaHeart/Midnight-Miqu-70B-v1.5-Safetensorsfix
LyraNovaHeart/Midnight-Miqu-70B-v1.5-Safetensorsfix is a 69 billion parameter DARE Linear merge model, derived from sophosympatheia/Midnight-Miqu-70B-v1.0 and migtissera/Tess-70B-v1.6. This uncensored model is specifically designed and optimized for high-quality roleplaying and storytelling tasks, offering a 32K token context length. It aims to improve upon Midnight Miqu v1.0 by passing certain tests without sacrificing writing quality, making it suitable for creative text generation.
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Midnight-Miqu-70B-v1.5-Safetensorsfix Overview
This model is a 69 billion parameter DARE Linear merge, combining the strengths of sophosympatheia/Midnight-Miqu-70B-v1.0 and migtissera/Tess-70B-v1.6. It maintains the core feel and performance of Midnight Miqu v1.0 while incorporating improvements from Tess, particularly in passing specific tests without compromising writing quality. The model supports a long context of up to 32,768 tokens, similar to its Miqu predecessors.
Key Capabilities & Features
- Optimized for Creative Writing: Specifically designed for high-quality roleplaying and storytelling.
- Uncensored: Provides unrestricted content generation, with users responsible for its output.
- Long Context Support: Capable of handling up to 32K tokens with
alpha_ropeset to 1. - Improved Performance: Addresses certain test failures of v1.0 while preserving writing quality.
- Sampler & Prompting Guidance: Includes detailed recommendations for sampler settings (e.g., Quadratic Sampling, Min-P) and prompting strategies (e.g., few-shot prompting, descriptive system messages) to optimize creative output.
Usage Considerations
- Personal Use Only: Due to its derivation from a leaked Mistral model, this merge is explicitly stated as suitable only for personal use, with no warranties or guarantees.
- "Warming Up" Required: May benefit from initial few-shot examples and descriptive system prompts to guide its writing style at the start of a new chat.
- Instruct Formats: Recommended for use with Vicuna or Mistral instruct formats.
Benchmarks
Evaluations on the Open LLM Leaderboard show an average score of 25.22, with specific metrics including IFEval (0-Shot) at 61.18 and BBH (3-Shot) at 38.54. More detailed results are available on the Hugging Face Open LLM Leaderboard.