LLama-2 7b Wu, Koo, Black, Blum, Scalzo, Kurtz
Model Description
LLama-2-WuKurtz is a state-of-the-art language model developed by Wu, Koo, Black, Blum, Scalzo, and Kurtz. It has been fine-tuned on our synthesized dataset comprising 80,000 training examples mastering nephrology. This model is apart of our paper Boosting Open-Sourced Large Language Models with Proprietary Imitation Learning [released soon!]
Training Data
The model was trained on a Nephrology synthesized dataset that was carefully curated and preprocessed. This dataset includes 80,000 examples that cover a wide range from imitation learning from proprietary LLMs, proprietary data, and lecture information, providing the model with a comprehensive understanding of Nephrology
Model Performance
Detailed performance metrics will be updated soon!
Usage
You can use this model for a variety of NLP tasks, including but not limited to text generation, text classification, sentiment analysis, and named entity recognition.
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("SeanWu25/llama-2-7b-WuKurtz")
model = AutoModelForCausalLM.from_pretrained("SeanWu25/llama-2-7b-WuKurtz")
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