Twi
Datasets
All datasets matching “Twi”test1TwitterHjerneRetrieval
TwitterHjerneRetrieval
An MTEB dataset
Massive Text Embedding Benchmark
Danish question asked on Twitter with the Hashtag #Twitterhjerne ('Twitter brain') and their corresponding answer.
Task category
t2t
Domains
Social, Written
Reference
https://huggingface.co/datasets/sorenmulli/da-hashtag-twitterhjerne
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/TwitterHjerneRetrieval.twittersemeval2015-pairclassification
TwitterSemEval2015
An MTEB dataset
Massive Text Embedding Benchmark
Paraphrase-Pairs of Tweets from the SemEval 2015 workshop.
Task category
t2t
Domains
Social, Written
Reference
https://alt.qcri.org/semeval2015/task1/
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(["TwitterSemEval2015"])
evaluator = mteb.MTEB(task)
model = mteb.get_model(YOUR_MODEL)… See the full description on the dataset page: https://huggingface.co/datasets/mteb/twittersemeval2015-pairclassification.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 to run… See the full description on the dataset page: https://huggingface.co/datasets/mteb/twitterurlcorpus-pairclassification.twitter-financial-news-sentiment
Dataset Description
The Twitter Financial News dataset is an English-language dataset containing an annotated corpus of finance-related tweets. This dataset is used to classify finance-related tweets for their sentiment.
The dataset holds 11,932 documents annotated with 3 labels:
sentiments = {
"LABEL_0": "Bearish",
"LABEL_1": "Bullish",
"LABEL_2": "Neutral"
}
The data was collected using the Twitter API. The current dataset supports the multi-class classification… See the full description on the dataset page: https://huggingface.co/datasets/zeroshot/twitter-financial-news-sentiment.twitch-chat
Twitch Chat Messages
Each Twitch channel is stored as its own dataset config, with its chat messages under data/<channel>/. Data arrives as small append-only chunk files (data/<channel>/<chunk-id>.jsonl) added on every publish cycle -- existing chunks are immutable and never re-uploaded, so cost per publish only scales with new messages, not the dataset's total size. Sharding chunks into a per-channel directory also keeps any single directory well under the Hub's 10… See the full description on the dataset page: https://huggingface.co/datasets/Daankular/twitch-chat.
