Transformers
PyTorch
Safetensors
English
t5
text2text-generation
finbert
financial-sentiment-analysis
sentiment-analysis
text-generation-inference
Instructions to use amphora/FinABSA-Longer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amphora/FinABSA-Longer with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("amphora/FinABSA-Longer") model = AutoModelForSeq2SeqLM.from_pretrained("amphora/FinABSA-Longer") - Notebooks
- Google Colab
- Kaggle
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- sentiment-analysis
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license:
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- apache-2.0
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## Model Description
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FinABSA-Longer is a T5-Large model trained for Aspect-Based Sentiment Analysis(ABSA) tasks using [SEntFiN 1.0](https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24634?af=R) and additional augmentation techniques. It shows robust behavior to even longer sequences compared to the previous [FinABSA model](https://huggingface.co/amphora/FinABSA). By replacing the target aspect with a [TGT] token the model predicts the sentiment concentrating to the aspect.[GitHub Repo](https://github.com/guijinSON/FinABSA)
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- sentiment-analysis
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license:
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- apache-2.0
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- amphora/FinABSA
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---
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## Model Description
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FinABSA-Longer is a T5-Large model trained for Aspect-Based Sentiment Analysis(ABSA) tasks using [SEntFiN 1.0](https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24634?af=R) and additional augmentation techniques. It shows robust behavior to even longer sequences compared to the previous [FinABSA model](https://huggingface.co/amphora/FinABSA). By replacing the target aspect with a [TGT] token the model predicts the sentiment concentrating to the aspect.[GitHub Repo](https://github.com/guijinSON/FinABSA)
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