Transformers
Safetensors
English
t5
text2text-generation
aspect-based-sentiment-analysis
absa
natural-language-processing
masked-absa
text-generation-inference
Instructions to use tweetpie/masked-absa-rest16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweetpie/masked-absa-rest16 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("tweetpie/masked-absa-rest16") model = AutoModelForSeq2SeqLM.from_pretrained("tweetpie/masked-absa-rest16") - Notebooks
- Google Colab
- Kaggle
Masking The Bias : From Echo Chambers to Large Scale Aspect-Based Sentiment Analysis
This repository addresses the challenges of scarcity and high costs associated with manual annotation in Aspect-Based Sentiment Analysis (ABSA) by utilizing weak supervision methods. We have demonstrated the superiority of our model using SemEval datasets and real-world tweet data.
For more details please visit github.com/tweetpie/masked-absa
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