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Topic modeling on abstracts of papers from the CShorten/ML-ArXiv-Papers dataset. Due to the lack of high-quality labeled data (and the idea of creating topics dynamically), we employ a knowledge distillation approach. A large teacher model (Llama-3-70B) generates labels for the dataset, and a smaller student model (Llama-3-8B) is fine-tuned on this data. The fine-tuned student model is then used for inference.

Model Details

Trained using custom metric: ROUGE score

Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

  • Developed by: Ankit Agrawal (ankitagr.nitb[@]gmail.com)
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  • Finetuned from model [optional]: meta-llama/Meta-Llama-3-8B-Instruct

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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Dataset used to train ankitagr01/llama_3_8b_ft_topic_new