bunnycore/Phi-4-RP-V0.2

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