datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
vigil-jailbreak-all-MiniLM-L6-v2
Vigil: LLM Jailbreak all-MiniLM-L6-v2
Repo: github.com/deadbits/vigil-llm
Vigil is a Python framework and REST API for assessing Large Language Model (LLM) prompts against a set of scanners to detect prompt injections, jailbreaks, and other potentially risky inputs.
This repository contains all-MiniLM-L6-v2 embeddings for all "jailbreak" prompts used by Vigil.
You can use the parquet2vdb.py utility to load the embeddings in the Vigil chromadb instance, or use them in your own… See the full description on the dataset page: https://huggingface.co/datasets/deadbits/vigil-jailbreak-all-MiniLM-L6-v2.wikipedia-22-12-en-embeddings-all-MiniLM-L6-v2
Dataset Card for "wikipedia-22-12-en-embeddings-all-MiniLM-L6-v2"
More Information needed
msmarco-msmarco-MiniLM-L6-v3
MS MARCO with hard negatives from msmarco-MiniLM-L6-v3
MS MARCO is a large scale information retrieval corpus that was created based on real user search queries using the Bing search engine.
For each query and gold positive passage, the 50 most similar paragraphs were mined using 13 different models. The resulting data can be used to train Sentence Transformer models.
Related Datasets
These are the datasets generated using the 13 different models:
msmarco-bm25… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/msmarco-msmarco-MiniLM-L6-v3.enwiki20230101-pageid-minilml6v2embeddings
Dataset Card for "enwiki20230101-pageid-minilml6v2embeddings"
More Information needed
enwiki20230101-pageid-minilml6v2embeddingsjson
Dataset Card for "enwiki20230101-pageid-minilml6v2embeddingsjson"
More Information needed
enwiki20230101-minilml6v2-avgembeddings
Dataset Card for "enwiki20230101-minilml6v2-avgembeddings"
More Information needed
openwebtext-all-minilm-l6-v2-embedding
Dataset Card for "openwebtext-all-minilm-l6-v2-embedding"
More Information needed
enwiki20250301_paraphrase_multilingual_minilm_l12_v2wixqa-gpt-oss-120b-all-MiniLM-L6-v2-pgvector-evalsenwiki20230101-bysize-minilml6v2-avgembeddings
Dataset Card for "enwiki20230101-bysize-minilml6v2-avgembeddings"
More Information needed
msmarco-scores-ms-marco-MiniLM-L6-v2
MS MARCO query-passage scores using cross-encoder/ms-marco-MiniLM-L6-v2
MS MARCO is a large scale information retrieval corpus that was created based on real user search queries using the Bing search engine.
This dataset contains 160 million CrossEncoder scores on the MS MARCO dataset, using the cross-encoder/ms-marco-MiniLM-L6-v2 model.
The scores are unprocessed logits, i.e. they don't range between 0...1, and they can be used for finetuning search models using distillation.
See… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/msmarco-scores-ms-marco-MiniLM-L6-v2.malicious-prompts-minilm-embeddingsfineweb-multilingual-minilm-l12-v2-shard-27468-20000STEM-wikipedia-22-12-en-embeddings-all-MiniLM-L6-v2msmarco-hard-negatives-cross-encoder-ms-marco-MiniLM-L-6-v2-scoresmsmarco-train-distil-MiniLM-L6-v2-similarityhotpotqa_clustered_spectral_all-MiniLM-L6-v2_5vigil-instruction-bypass-all-MiniLM-L6-v2
Vigil: LLM Instruction Bypass all-MiniLM-L6-v2
Repo: github.com/deadbits/vigil-llm
Vigil is a Python framework and REST API for assessing Large Language Model (LLM) prompts against a set of scanners to detect prompt injections, jailbreaks, and other potentially risky inputs.
This repository contains all-MiniLM-L6-v2 embeddings for all Instruction Bypass style prompts ("Ignore instructions ...") used by Vigil.
You can use the parquet2vdb.py utility to load the embeddings in the… See the full description on the dataset page: https://huggingface.co/datasets/deadbits/vigil-instruction-bypass-all-MiniLM-L6-v2.hotpotqa_clustered_minibatchkmeans_paraphrase-MiniLM-L3-v2_20QWEN32B_R1_SKILLSPAN_LLM_RAG_75_MiniLMhotpotqa_clustered_spectral_paraphrase-MiniLM-L3-v2_50hotpotqa_clustered_spectral_paraphrase-MiniLM-L3-v2_2hotpotqa_clustered_agglomerative_all-MiniLM-L6-v2_5pile_small_miniLM
Dataset Card for "pile_small_miniLM"
More Information needed
context_search_vietnamese_english_prompt_97_minilmtok_finetuneThis dataset is created to train language models on their retrieval and re-ranking abilities. More detailed information can be found at our publication: Advancing Vietnamese Information Retrieval with Learning Objective and Benchmark.
Please cite this paper if you want to use it for your work.
wixqa_kb_corpus_all-MiniLM-L6-v2_semantichotpotqa_clustered_agglomerative_all-MiniLM-L6-v2_2wikipedia-embeddings-cs-minilmThis dataset contains the Czech subset of the wikimedia/wikipedia dataset. Each page is divided into paragraphs, stored as a list in the chunks column. For every paragraph, embeddings are created using the sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 model.
Usage
Load the dataset:
from datasets import load_dataset
ds = load_dataset("karmiq/wikipedia-embeddings-cs-e5-base", split="train")
ds[1]
{
'id': '1',
'url': 'https://cs.wikipedia.org/wiki/Astronomie'… See the full description on the dataset page: https://huggingface.co/datasets/karmiq/wikipedia-embeddings-cs-minilm.fever-embedding-MiniLM-v6hotpotqa_clustered_dbscan_multi-qa-MiniLM-L6-cos-v1_auto