Create README.md

README.md

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+---
+license: mit
+datasets:
+- cardiffnlp/super_tweeteval
+language:
+- en
+pipeline_tag: text-classification
+---
+# cardiffnlp/twitter-roberta-large-latest-tweet-hate
+
+
+This is a RoBERTa-large model trained on 154M tweets until the end of December 2022 and finetuned for hate speech detection (multiclass classification) on the _TweetHate_ 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).
+
+# Labels
+<code>
+"id2label": {
+  "0": "hate_gender",
+  "1": "hate_race",  
+  "2": "hate_sexuality",  
+  "3": "hate_religion",  
+  "4": "hate_origin",  
+  "5": "hate_disability",  
+  "6": "hate_age",  
+  "7": "not_hate"
+}
+</code>
+
+## Example
+```python
+from transformers import pipeline
+text = 'Eid Mubarak Everyone!!! ❤ May Allah unite all Muslims, show us the right path, and bless us with good health.❣'
+
+pipe = pipeline('text-classification', model="cardiffnlp/twitter-roberta-large-latest-tweet-hate")
+pipe(text)
+>> [{'label': 'not_hate', 'score': 0.9997966885566711}]
+```
+
+## 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}
+}
+```