castorini/rank_vicuna_7b_v1_fp16
RankVicuna is a 7 billion parameter chat assistant developed by Castorini, fine-tuned from Llama 2 on user-shared conversations from ShareGPT. This FP16 variant is specifically designed for research at the intersection of large language models and retrieval, leveraging data augmentation during its training process. It is optimized for tasks related to natural language processing and information retrieval, making it suitable for researchers and hobbyists in these fields.
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RankVicuna: A Retrieval-Focused Chat Assistant
RankVicuna is a 7 billion parameter chat assistant developed by Castorini, built upon the Llama 2 architecture. It is fine-tuned from lmsys/vicuna-7b-v1.5 using supervised instruction fine-tuning on user-shared conversations collected from ShareGPT, with additional data augmentation. This specific model is provided in FP16 precision.
Key Capabilities
- Chat Assistant: Functions as a conversational AI, leveraging its training on diverse user interactions.
- Retrieval Research: Primarily intended for research applications combining large language models with information retrieval techniques.
- Llama 2 Base: Benefits from the foundational capabilities of the Llama 2 model family.
Good For
- Researchers: Ideal for those exploring the intersection of LLMs and retrieval, as detailed in its accompanying paper.
- Hobbyists: Suitable for individuals interested in natural language processing and information retrieval projects.
- Experimental Setups: Provides a fine-tuned model for evaluating and developing new approaches in these domains, with evaluations conducted on datasets like DL19/DL20.