Instructions to use cardiffnlp/twitter-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cardiffnlp/twitter-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="cardiffnlp/twitter-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base") model = AutoModelForMaskedLM.from_pretrained("cardiffnlp/twitter-roberta-base") - Inference
- Notebooks
- Google Colab
- Kaggle
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# Twitter-roBERTa-base
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## Preprocess Text
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# Twitter-roBERTa-base
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This is a RoBERTa-base model trained on ~58M tweets on top of the original RoBERTa-base checkpoint, as described and evaluated in the [_TweetEval_ benchmark (Findings of EMNLP 2020)](https://arxiv.org/pdf/2010.12421.pdf).
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To evaluate this and other LMs on Twitter-specific data, please refer to the [Tweeteval official repository](https://github.com/cardiffnlp/tweeteval).
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## Preprocess Text
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