mteb/twitterurlcorpus-pairclassification
TwitterURLCorpus An MTEB dataset Massive Text Embedding Benchmark Paraphrase-Pairs of Tweets. Task category t2t Domains Social, Written Reference https://languagenet.github.io/ How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: import mteb task = mteb.get_tasks(["TwitterURLCorpus"]) evaluator = mteb.MTEB(task) model = mteb.get_model(YOUR_MODEL) evaluator.run(model) To learn more about how… See the full description on the dataset page: https://huggingface.co/datasets/mteb/twitterurlcorpus-pairclassification.
| Author / organization | mteb |
|---|---|
| License (as declared) | unknown |
| Downloads | 5K (as reported by Hugging Face) |
| Likes | 0 |
| Created | 19 April 2022 |
| Last updated at source | 24 February 2026 |
Popularity, last 2 days
5,000 now (-103 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Recent changes
- 17 Oct 2026 Description: TwitterURLCorpus An MTEB dataset Massive Text Embedding Benchmark Paraphrase-Pairs of Tweets. Task category t2t Domains Social, Written Reference https://languagenet.github.io/ How to evaluate on this task You can evaluate an embedding mode → TwitterURLCorpus An MTEB dataset Massive Text Embedding Benchmark Paraphrase-Pairs of Tweets. Task category t2t Domains Social, Written Reference https://languagenet.github.io/ How to evaluate on this task You can evaluate an embedding mode
Changes detected by Silytics between refreshes of the source.
More from mteb
- mteb/resultsDataset
- mteb/sts12-stsDataset
- mteb/nfcorpusDataset
- mteb/banking77Dataset
- mteb/amazon_massive_intentDataset
- mteb/scifactDataset
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.