Update README 2022
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# Twitter-roBERTa-base for Sentiment Analysis - UPDATED (2021)
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# Twitter-roBERTa-base for Sentiment Analysis - UPDATED (2022)
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This is a roBERTa-base model trained on ~124M tweets from January 2018 to December 2021 (see [here](https://huggingface.co/cardiffnlp/twitter-roberta-base-2021-124m)), and finetuned for sentiment analysis with the TweetEval benchmark.
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This is a RoBERTa-base model trained on ~124M tweets from January 2018 to December 2021, and finetuned for sentiment analysis with the TweetEval benchmark.
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The original roBERTa-base model can be found [here](https://huggingface.co/cardiffnlp/twitter-roberta-base-2021-124m) and the original reference paper is [TweetEval](https://github.com/cardiffnlp/tweeteval). This model is suitable for English.
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The original Twitter-based RoBERTa model can be found [here](https://huggingface.co/cardiffnlp/twitter-roberta-base-2021-124m) and the original reference paper is [TweetEval](https://github.com/cardiffnlp/tweeteval). This model is suitable for English.
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- Reference Paper: [TimeLMs paper](https://arxiv.org/abs/2202.03829).
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- Reference Paper: [TimeLMs paper](https://arxiv.org/abs/2202.03829).
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- Git Repo: [TimeLMs official repository](https://github.com/cardiffnlp/timelms).
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- Git Repo: [TimeLMs official repository](https://github.com/cardiffnlp/timelms).
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@ -18,6 +18,8 @@ The original roBERTa-base model can be found [here](https://huggingface.co/cardi
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1 -> Neutral;
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1 -> Neutral;
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2 -> Positive
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2 -> Positive
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This sentiment analysis model has been integrated into [TweetNLP](https://github.com/cardiffnlp/tweetnlp). You can access the demo [here](https://tweetnlp.org).
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## Example Pipeline
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## Example Pipeline
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```python
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```python
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from transformers import pipeline
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from transformers import pipeline
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