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--- |
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library_name: transformers |
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tags: |
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- news analytics |
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- cryptocurrency |
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- crypto |
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- Bitcoin |
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- Ethereum |
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- Seq2Seq |
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language: |
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- en |
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base_model: |
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- facebook/bart-large |
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--- |
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# Seq2Seq Model bpavlsh/bart-crypto-summary |
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### Model Description |
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Fine-tuned Seq2Seq model is developed for analysing and summarization of cryptocurrency news for the following crypto coins: |
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Bitcoin, Ethereum, Tether, Solana, Binance Coin. Max input size for texts is 1024 tokens that is about |
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3.5K chars of texts. Model is created by fine-tuning facebook/bart-large transformer model. |
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Model outputs short text summary and uptrend/downtrend lists of specified above crypto coins if their trends are considered in the news text. |
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## How to Get Started with the Model |
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Use the code below to get started with the model: |
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```python |
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summarizer = pipeline("summarization", model = "bpavlsh/bart-crypto-summary") |
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txt=""" |
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Crypto market shows mixed signals. Bitcoin (BTC) and Ethereum (ETH) is experiencing a slight downturn, weighed down by bearish |
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investor sentiment, while Solana (SOL) see sharp uptrends driven by increased on-chain activity. |
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""" |
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result=summarizer(txt, early_stopping=True)[0]['summary_text'] |
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print(result) |
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Result: |
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""" |
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Bitcoin and Ethereum are experiencing a slight downturn with bearish investor sentiment, while Solana shows a strong uptrend driven by increased on-chain activity. |
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Uptrend: Solana. |
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Downtrend: Bitcoin, Ethereum. |
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""" |
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``` |
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## Disclaimer |
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We are sharing a considered model and results for academic purpose only, |
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not any financial advice or recommendations for real business or investment. |
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## Contacts |
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B. Pavlyshenko https://www.linkedin.com/in/bpavlyshenko |
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## References |
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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 |
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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 |
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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 |
