cluster
jina-embeddings-v5-text-nano-clusteringjina-embeddings-v5-text-small-clusteringjina-embeddings-v5-omni-nano-clustering-GGUFNickyNicky_-_TinyDolphin-2.8-1.1b_oasst2_chatML_all_Cluster_dare_ties_v1-ggufjina-embeddings-v5-text-small-clustering-GGUFjina-embeddings-v5-omni-small-clustering-GGUFNickyNicky-gemma-2b-it_oasst2_chatML_Cluster_1_V1-GGUFNickyNicky_-_Mixtral-4x1.1B-TinyDolphin-2.8-1.1b_oasst2_chatML_Cluster-gguf
Datasets
All datasets matching “cluster”twentynewsgroups-clustering
TwentyNewsgroupsClustering.v2
An MTEB dataset
Massive Text Embedding Benchmark
Clustering of the 20 Newsgroups dataset (subject only).
Task category
t2c
Domains
News, Written
Reference
https://scikit-learn.org/0.19/datasets/twenty_newsgroups.html
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(["TwentyNewsgroupsClustering.v2"])
evaluator = mteb.MTEB(task)… See the full description on the dataset page: https://huggingface.co/datasets/mteb/twentynewsgroups-clustering.stackexchange-clustering
StackExchangeClustering.v2
An MTEB dataset
Massive Text Embedding Benchmark
Clustering of titles from 121 stackexchanges. Clustering of 25 sets, each with 10-50 classes, and each class with 100 - 1000 sentences.
Task category
t2c
Domains
Web, Written
Reference
https://arxiv.org/abs/2104.07081
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/stackexchange-clustering.arxiv-clustering-s2s
ArXivHierarchicalClusteringS2S
An MTEB dataset
Massive Text Embedding Benchmark
Clustering of titles from arxiv. Clustering of 30 sets, either on the main or secondary category
Task category
t2c
Domains
Academic, Written
Reference
https://www.kaggle.com/Cornell-University/arxiv
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(["ArXivHierarchicalClusteringS2S"])… See the full description on the dataset page: https://huggingface.co/datasets/mteb/arxiv-clustering-s2s.biorxiv-clustering-p2p
BiorxivClusteringP2P.v2
An MTEB dataset
Massive Text Embedding Benchmark
Clustering of titles+abstract from biorxiv across 26 categories.
Task category
t2c
Domains
Academic, Written
Reference
https://api.biorxiv.org/
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(["BiorxivClusteringP2P.v2"])
evaluator = mteb.MTEB(task)
model = mteb.get_model(YOUR_MODEL)… See the full description on the dataset page: https://huggingface.co/datasets/mteb/biorxiv-clustering-p2p.medrxiv-clustering-s2s
MedrxivClusteringS2S.v2
An MTEB dataset
Massive Text Embedding Benchmark
Clustering of titles from medrxiv across 51 categories.
Task category
t2c
Domains
Academic, Medical, Written
Reference
https://api.medrxiv.org/
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(["MedrxivClusteringS2S.v2"])
evaluator = mteb.MTEB(task)
model = mteb.get_model(YOUR_MODEL)… See the full description on the dataset page: https://huggingface.co/datasets/mteb/medrxiv-clustering-s2s.arxiv-clustering-p2p
ArXivHierarchicalClusteringP2P
An MTEB dataset
Massive Text Embedding Benchmark
Clustering of titles+abstract from arxiv. Clustering of 30 sets, either on the main or secondary category
Task category
t2c
Domains
Academic, Written
Reference
https://www.kaggle.com/Cornell-University/arxiv
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/arxiv-clustering-p2p.