Instructions to use tungwongchi/mRP-LLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tungwongchi/mRP-LLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="tungwongchi/mRP-LLM", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tungwongchi/mRP-LLM", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Role-playing in conversational AI allows for the simulation of various characters and scenarios, providing rich and diverse interactions. We propose mRP-LLM, a novel approach that integrates multiple role-playing characters into a single model to maximize resource efficiency and expand the model's conversational capabilities.
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