datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
transformers-pr
Transformers PR Dataset
Normalized snapshots of issues, pull requests, comments, reviews, and linkage data from huggingface/transformers.
Files:
issues.parquet
pull_requests.parquet
comments.parquet
issue_comments.parquet (derived view of issue discussion comments)
pr_comments.parquet (derived view of pull request discussion comments)
reviews.parquet
pr_files.parquet
pr_diffs.parquet
review_comments.parquet
links.parquet
events.parquet
new_contributors.parquet… See the full description on the dataset page: https://huggingface.co/datasets/evalstate/transformers-pr.msmarco-distilbert-margin-mse-mean-dot-v1
MS MARCO with hard negatives from distilbert-margin-mse-mean-dot-v1
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:… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/msmarco-distilbert-margin-mse-mean-dot-v1.transformers-pr-slop-dataset
Transformers PR Slop Dataset
Normalized snapshots of issues, pull requests, comments, reviews, and linkage data from huggingface/transformers.
Files:
issues.parquet
pull_requests.parquet
comments.parquet
issue_comments.parquet (derived view of issue discussion comments)
pr_comments.parquet (derived view of pull request discussion comments)
pr_files.parquet
pr_diffs.parquet
reviews.parquet
review_comments.parquet
links.parquet
events.parquet
Use:
duplicate PR and issue… See the full description on the dataset page: https://huggingface.co/datasets/burtenshaw/transformers-pr-slop-dataset.smiles-transformers
smiles-transformers dataset
TODO: Add references to the datasets we curated
dataset features
name: text
Molecule SMILES : string
name: formula
Molecular formula : string
name: NumHDonors
Number of hidrogen bond donors : int
name: NumHAcceptors
Number of hidrogen bond acceptors : int
name: MolLogP
Wildman-Crippen LogP : float
name: NumHeteroatoms
Number of hetero atoms: int
name: RingCount
Number of rings : int
name: NumRotatableBonds
Number of rotable… See the full description on the dataset page: https://huggingface.co/datasets/maykcaldas/smiles-transformers.msmarco-bm25
MS MARCO with hard negatives from bm25
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-bm25.msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1
MS MARCO with hard negatives from co-condenser-margin-mse-sym-mnrl-mean-v1
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:… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1.msmarco-msmarco-distilbert-base-v3
MS MARCO with hard negatives from msmarco-distilbert-base-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-distilbert-base-v3.msmarco-distilbert-margin-mse-sym-mnrl-mean-v2
MS MARCO with hard negatives from distilbert-margin-mse-sym-mnrl-mean-v2
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:… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/msmarco-distilbert-margin-mse-sym-mnrl-mean-v2.msmarco-msmarco-distilbert-base-tas-b
MS MARCO with hard negatives from msmarco-distilbert-base-tas-b
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:… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/msmarco-msmarco-distilbert-base-tas-b.msmarco-mpnet-margin-mse-mean-v1
MS MARCO with hard negatives from mpnet-margin-mse-mean-v1
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-mpnet-margin-mse-mean-v1.msmarco-distilbert-margin-mse-cls-dot-v1
MS MARCO with hard negatives from distilbert-margin-mse-cls-dot-v1
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:… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/msmarco-distilbert-margin-mse-cls-dot-v1.msmarco-distilbert-margin-mse-sym-mnrl-mean-v1
MS MARCO with hard negatives from distilbert-margin-mse-sym-mnrl-mean-v1
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:… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/msmarco-distilbert-margin-mse-sym-mnrl-mean-v1.transformers-dependents
transformers metrics
This dataset contains metrics about the huggingface/transformers package.
Number of repositories in the dataset: 27067
Number of packages in the dataset: 823
Package dependents
This contains the data available in the used-by
tab on GitHub.
Package & Repository star count
This section shows the package and repository star count, individually.
Package
Repository
There are 65 packages that have more than 1000 stars.
There are 140… See the full description on the dataset page: https://huggingface.co/datasets/open-source-metrics/transformers-dependents.msmarco-distilbert-margin-mse-mnrl-mean-v1
MS MARCO with hard negatives from distilbert-margin-mse-mnrl-mean-v1
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:… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/msmarco-distilbert-margin-mse-mnrl-mean-v1.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.msmarco-co-condenser-margin-mse-cls-v1
MS MARCO with hard negatives from co-condenser-margin-mse-cls-v1
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:… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/msmarco-co-condenser-margin-mse-cls-v1.msmarco-distilbert-margin-mse-cls-dot-v2
MS MARCO with hard negatives from distilbert-margin-mse-cls-dot-v2
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:… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/msmarco-distilbert-margin-mse-cls-dot-v2.transformers-coding-session-captures
dacorvo/transformers-coding-session-captures
HTTP captures of agent ↔ model interactions — one parquet row per
/v1/chat/completions call. Produced by
agentcap.
Native session traces for the same runs live in companion datasets
named transformers-coding-session-<agent>-traces. They're all grouped under the
transformers-coding-session Collection
alongside this dataset. Join on run_id.
Loading
from datasets import load_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/dacorvo/transformers-coding-session-captures.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.Transformers-Github-Issuestransformers-issues-corpusadversarial-vision-transformerstransformers-issues
HuggingFace Transformers GitHub Issues Dataset
Dataset Description
This dataset contains all issues and pull requests (open and closed) from the huggingface/transformers GitHub repository, along with their comment threads. It was collected on July 19-20, 2026 via the GitHub REST API and follows the workflow described in the Hugging Face NLP course — Creating your own dataset.
Repository: huggingface/transformers
Total rows: 41,618 (issues + pull requests)
Date… See the full description on the dataset page: https://huggingface.co/datasets/noamaanMulla-03/transformers-issues.transformers-issuesJust dummy dataset with transformers lib issues on GitHub.
synthetic-pretraining-transformers-v1
Synthetic Pre-training Transformers v1.0.0
Dataset Description
This is a synthetic pre-training dataset generated from transformer architecture patterns. It contains paraphrased, augmented, and interpolated content derived from validated seed data about neural sequence modeling and attention mechanisms.
Dataset Summary
Total Samples: 100
Total Tokens: 6,084
Average Tokens per Sample: 60.84
Format: Parquet
Version: 1.0.0
License: CC-BY-4.0
Supported… See the full description on the dataset page: https://huggingface.co/datasets/gugarosa/synthetic-pretraining-transformers-v1.hf-hub-transformers
adversarial-vision-transformers-robustnesssemantic-transformerstransformers_rag_no_feature_llama70b_llama8b_resultsResults for RAG without LLM generated features transformers code using queries provided by HuggingFace team.
Description
The RAG responses are generated using the dataset: https://huggingface.co/datasets/Nutanix/transformers_processed_data_llama70b. Llama-3-128k-70b-Instruct-awq was used for feature extraction of transformers code(v4.42.3) to create the dataset, and Llama-3-8b-Instruct was used for generation of both RAG and Raw outputs.
Data Fields
id - The id for the… See the full description on the dataset page: https://huggingface.co/datasets/Nutanix/transformers_rag_no_feature_llama70b_llama8b_results.transformers_mpnet_rag_llama70b_llama8b_results