library_name: transformers
tags: []
Model Card for Model bpavlsh/bart-crypto-summary
Model Description
Fine-tuned model for analysing cryptocurrency news for the following crypto coins: Bitcoin, Ethereum, Tether, Solana, Binance Coin. Max input size for texts is 1024 tokens that is about 3.5K chars of texts. Model is created by fine-tuning facebook/bart-large transformer model. Model outputs short text summary and uptrend/downtrend lists of crypto coins.
How to Get Started with the Model
Use the code below to get started with the model:
summarizer = pipeline("summarization", model = "bpavlsh/bart-crypto-summary") txt=""" Crypto market shows mixed signals. Bitcoin (BTC) and Ethereum (ETH) is experiencing a slight downturn, weighed down by bearish investor sentiment, while Solana (SOL) see sharp uptrends driven by increased on-chain activity. """ result=summarizer(txt, early_stopping=True)[0]['summary_text'] print(result)
Result: Bitcoin and Ethereum are experiencing a slight downturn with bearish investor sentiment, while Solana shows a strong uptrend driven by increased on-chain activity. Uptrend: Solana. Downtrend: Bitcoin, Ethereum.
Disclaimer
We are sharing a considered approach, ideas and results for academic purpose only, not any financial advice or recommendations for real business or investment.
Model Card Contact
B. Pavlyshenko https://www.linkedin.com/in/bpavlyshenko
References
Pavlyshenko B.M. Financial News Analytics Using Fine-Tuned Llama 2 GPT Model. arXiv preprint arXiv:2308.13032. 2023. Download PDF: https://arxiv.org/pdf/2308.13032.pdf
Pavlyshenko B.M. Analysis of Disinformation and Fake News Detection Using Fine-Tuned Large Language Model. arXiv preprint arXiv:2309.04704. 2023. Download PDF: https://arxiv.org/pdf/2309.04704.pdf
Pavlyshenko, B.M. Bitcoin Price Predictive Modeling Using Expert Correction. 2019 XIth International Scientific and Practical Conference on Electronics and Information Technologies (ELIT), September 16 – 18, 2019 Lviv, Ukraine, pages: 163-167. Download PDF: https://arxiv.org/pdf/2201.02729