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-topic
+
+This is a RoBERTa-large model trained on 154M tweets until the end of December 2022 and finetuned for topic classification (multilabel classification) on the _TweetTopic_ 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": "arts_&_culture",
+    "1": "business_&_entrepreneurs",
+    "2": "celebrity_&_pop_culture",
+    "3": "diaries_&_daily_life",
+    "4": "family",
+    "5": "fashion_&_style",
+    "6": "film_tv_&_video",
+    "7": "fitness_&_health",
+    "8": "food_&_dining",
+    "9": "gaming",
+    "10": "learning_&_educational",
+    "11": "music",
+    "12": "news_&_social_concern",
+    "13": "other_hobbies",
+    "14": "relationships",
+    "15": "science_&_technology",
+    "16": "sports",
+    "17": "travel_&_adventure",
+    "18": "youth_&_student_life"
+  }
+</code>
+
+
+## Example
+```python
+from transformers import pipeline
+text = "So @AB is just the latest victim of the madden curse. If you’re on the cover of that game your career will take a turn for the worse"
+
+pipe = pipeline('text-classification', model="cardiffnlp/twitter-roberta-large-latest-tweet-topic", return_all_scores=True)
+predictions = pipe(text)[0]
+predictions = [x for x in predictions if x['score'] > 0.5]
+predictions
+>> [{'label': 'gaming', 'score': 0.899931013584137},
+ {'label': 'sports', 'score': 0.5215537548065186}]
+```
+
+## 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}
+}
+```