ParasiticRogue/Magnum-Instruct-DPO-12B

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:12BQuant:FP8Ctx Length:32kPublished:Aug 16, 2024License:apache-2.0Architecture:Transformer0.0K Open Weights Warm

Magnum-Instruct-DPO-12B by ParasiticRogue is a 12 billion parameter instruction-tuned causal language model, built from a 50/50 merge of Mistral-Nemo variants that underwent additional DPO/ORPO training. This model is designed for conversational AI, excelling in persona adherence, detailed environmental descriptions, and dynamic narrative progression, particularly suited for uncensored and immersive chat applications with a specific system prompt structure. It features a 32768 token context length, making it suitable for extended interactions and complex scenarios.

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Overview

Magnum-Instruct-DPO-12B is a 12 billion parameter instruction-tuned language model developed by ParasiticRogue. It is a 50/50 merge of two pre-trained Mistral-Nemo variants (mistral-nemo-bophades-12B and mistral-nemo-gutenberg-12B-v3) that have undergone additional DPO/ORPO (Direct Preference Optimization/Odds Ratio Preference Optimization) training. This approach aims to enhance the model's ability to follow instructions and generate preferred responses.

Key Capabilities

  • Enhanced Instruction Following: Benefits from DPO/ORPO training on its base models, suggesting improved alignment with user preferences.
  • Immersive Conversational AI: Optimized for detailed, uncensored, and dynamic chat interactions, as indicated by its specific system prompt.
  • Persona Adherence: Designed to maintain a consistent character persona, including subtle gestures, quirks, and humor.
  • Contextual Awareness: Emphasizes vivid environmental descriptions, emotional depth, and logical narrative progression within a 32768 token context.

Good For

This model is particularly well-suited for applications requiring highly interactive and immersive chat experiences, such as role-playing, creative writing assistance, or virtual companions where detailed character portrayal and dynamic storytelling are crucial. Its training and prompt format suggest a strong focus on generating coherent, engaging, and contextually rich responses in extended conversations.

Popular Sampler Settings

Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.

temperature
top_p
top_k
frequency_penalty
presence_penalty
repetition_penalty
min_p