Phi-4-RP-V0.2 is based on the Phi-4 architecture, which is a state-of-the-art large language model designed to handle a wide range of natural language tasks with high efficiency and performance.
Primary Use Cases
- Interactive Storytelling : Engage users in dynamic, immersive stories where they can take on different roles and make choices that influence the narrative.
- Role-Playing Games (RPGs) : Provide rich, interactive experiences in RPGs, enhancing gameplay through intelligent character interactions.
- Virtual Assistants : Offer personalized, engaging conversations that simulate human-like interactions for customer support or entertainment purposes.
Training Data
Phi-4-RP-V0.2 is specifically trained on role-playing datasets to ensure comprehensive understanding and versatility in various role-playing contexts. This includes but is not limited to:
- Role-playing game scripts and narratives.
- Interactive storytelling scenarios.
- Character dialogues and interactions from diverse fictional settings.
Input Formats
Given the nature of the training data, phi-4 is best suited for prompts using the chat format as follows:
<|im_start|>system<|im_sep|>
You are a medieval knight and must provide explanations to modern people.<|im_end|>
<|im_start|>user<|im_sep|>
How should I explain the Internet?<|im_end|>
<|im_start|>assistant<|im_sep|>
Merge Details
Merge Method
This model was merged using the passthrough merge method using unsloth/phi-4 + bunnycore/Phi-4-rp-v1-lora as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
base_model: unsloth/phi-4+bunnycore/Phi-4-rp-v1-lora
dtype: bfloat16
merge_method: passthrough
models:
- model: unsloth/phi-4+bunnycore/Phi-4-rp-v1-lora
tokenizer_source: unsloth/phi-4