Create README.md

README.md

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+---
+license: mit
+datasets:
+- cardiffnlp/super_tweeteval
+language:
+- en
+pipeline_tag: sentence-similarity
+---
+# cardiffnlp/twitter-roberta-large-latest-tweet-similarity
+
+This is a RoBERTa-large model trained on 154M tweets until the end of December 2022 and finetuned for tweet similarity (regression on two texts) on the _TweetSIM_ dataset of [SuperTweetEval](https://huggingface.co/datasets/cardiffnlp/super_tweeteval).
+The original Twitter-based RoBERTa model can be found [here](https://huggingface.co/cardiffnlp/twitter-roberta-large-2022-154m).
+
+## Example
+```python
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model_name = "cardiffnlp/twitter-roberta-large-latest-tweet-intimacy"
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+
+text_1 = 'Looooooool what is this story #TalksWithAsh'
+text_2 = 'For someone who keeps saying long story short, the story is quite long iyah #TalksWithAsh'
+
+text_input = f"{text_1} </s> {text_2}"
+
+model(**tokenizer(text_input, return_tensors="pt")).logits
+>>tensor([[2.9565]])
+```
+
+
+## Citation Information
+Please cite the [reference paper](https://arxiv.org/abs/2310.14757) if you use this model.
+
+```bibtex
+@inproceedings{antypas2023supertweeteval,
+  title={SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research},
+  author={Dimosthenis Antypas and Asahi Ushio and Francesco Barbieri and Leonardo Neves and Kiamehr Rezaee and Luis Espinosa-Anke and Jiaxin Pei and Jose Camacho-Collados},
+  booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023},
+  year={2023}
+}
+```