Instructions to use helinivan/multilingual-sarcasm-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use helinivan/multilingual-sarcasm-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="helinivan/multilingual-sarcasm-detector")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("helinivan/multilingual-sarcasm-detector") model = AutoModelForSequenceClassification.from_pretrained("helinivan/multilingual-sarcasm-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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--- language: "multilingual" tags: - bert - sarcasm-detection - text-classification widget: - text: "CIA Realizes It's Been Using Black Highlighters All These Years." --- # Multilingual Sarcasm Detector Multilingual Sarcasm Detector is a text classification model built to detect sarcasm from news article titles. It is fine-tuned on bert-multilingual uncased and the training data consists of ready-made datasets available on Kaggle as well scraped data from multiple newspapers in English, Dutch and Italian. ## Metrics: ## Training Data Datasets: - English language data: [Kaggle: News Headlines Dataset For Sarcasm Detection]([https://www.kaggle.com/datasets/rmisra/news-headlines-dataset-for-sarcasm-detection]). - Dutch non-sarcastic data: [Kaggle: Dutch News Articles]([https://www.kaggle.com/datasets/maxscheijen/dutch-news-articles]) Scraped data: - Dutch sarcastic news from [De Speld]([https://speld.nl]) - Italian non-sarcastic news from [Il Giornale]([https://www.ilgiornale.it])…6146e12 -
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