datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
rubygems-20230301rubygems-20241031Stack2Graph_KG_ruby
Ruby StackOverflow Knowledge Graph
Summary
This Hugging Face dataset repository contains the Ruby shard of the Stack2Graph StackOverflow Knowledge Graph.
Hugging Face uses one dataset repository per programming language, so this repository is directly cloneable without an extra top-level archive wrapper.
The artifact is optimized for graph-based retrieval, SPARQL analytics, and retrieval-augmented question answering over Stack Overflow content.
Stack2Graph source:… See the full description on the dataset page: https://huggingface.co/datasets/Mo7art/Stack2Graph_KG_ruby.ml-table-retrieval-benchmarks
ML Table Retrieval Benchmarks
Benchmark data for ml-table-retrieval: queries, database schemas, and SQLite databases for evaluating table-set retrieval and reranking.
Download everything with:
pip install huggingface_hub
python -c "from huggingface_hub import snapshot_download; snapshot_download('Rubyando59/ml-table-retrieval-benchmarks', repo_type='dataset', local_dir='data')"
or, from inside the ml-table-retrieval repo, python scripts/download_data.py (pulls only the splits… See the full description on the dataset page: https://huggingface.co/datasets/Rubyando59/ml-table-retrieval-benchmarks.marin-starcoderdata_rubycornstack-ruby-v1
CoRNStack Ruby Dataset
The CoRNStack Dataset, accepted to ICLR 2025, is a large-scale high quality training dataset specifically for code retrieval across multiple
programming languages. This dataset comprises of <query, positive, negative> triplets used to train nomic-embed-code,
CodeRankEmbed, and CodeRankLLM.
CoRNStack Dataset Curation
Starting with the deduplicated Stackv2, we create text-code pairs from function docstrings and respective code. We filtered out… See the full description on the dataset page: https://huggingface.co/datasets/nomic-ai/cornstack-ruby-v1.cornstack_ruby_ru_enThe CoRNStack Dataset translated into Russian. Translation was done with Qwen3-8B model.
Ruby-Gillman-Teenage-KrakenCodeSearchNet-ruby-qrelsEmploying the CoIR evaluation framework's dataset version, utilize the code below for assessment:
import coir
from coir.data_loader import get_tasks
from coir.evaluation import COIR
from coir.models import YourCustomDEModel
model_name = "intfloat/e5-base-v2"
# Load the model
model = YourCustomDEModel(model_name=model_name)
# Get tasks
#all task ["codetrans-dl","stackoverflow-qa","apps","codefeedback-mt","codefeedback-st","codetrans-contest","synthetic-
# text2sql","cosqa","codesearchnet"… See the full description on the dataset page: https://huggingface.co/datasets/CoIR-Retrieval/CodeSearchNet-ruby-qrels.details_Yuma42__KangalKhan-Beta-Ruby-7B
Dataset Card for Evaluation run of Yuma42/KangalKhan-Beta-Ruby-7B
Dataset automatically created during the evaluation run of model Yuma42/KangalKhan-Beta-Ruby-7B on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_Yuma42__KangalKhan-Beta-Ruby-7B.CodeSearchNet-ruby-queries-corpus
Dataset Card for "CodeSearchNet-ruby-queries-corpus"
More Information needed
codexglue_code2text_ruby
Dataset Card for "codexglue_code2text_ruby"
More Information needed
code-text-ruby
Dataset is imported from CodeXGLUE and pre-processed using their script.
Where to find in Semeru:
The dataset can be found at /nfs/semeru/semeru_datasets/code_xglue/code-to-text/ruby in Semeru
CodeXGLUE -- Code-To-Text
Task Definition
The task is to generate natural language comments for a code, and evaluted by smoothed bleu-4 score.
Dataset
The dataset we use comes from CodeSearchNet and we filter the dataset as the following:
Remove… See the full description on the dataset page: https://huggingface.co/datasets/semeru/code-text-ruby.details_Yuma42__KangalKhan-Ruby-7B
Dataset Card for Evaluation run of Yuma42/KangalKhan-Ruby-7B
Dataset automatically created during the evaluation run of model Yuma42/KangalKhan-Ruby-7B on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_Yuma42__KangalKhan-Ruby-7B.code-search-net-ruby
Dataset Card for "code-search-net-ruby"
Dataset Summary
This dataset is the Ruby portion of the CodeSarchNet annotated with a summary column.The code-search-net dataset includes open source functions that include comments found at GitHub.The summary is a short description of what the function does.
Languages
The dataset's comments are in English and the functions are coded in Ruby
Data Splits
Train, test, validation labels are included in the… See the full description on the dataset page: https://huggingface.co/datasets/Nan-Do/code-search-net-ruby.the-stack-ruby-clean
Dataset 1: TheStack - Ruby - Cleaned
Description: This dataset is drawn from TheStack Corpus, an open-source code dataset with over 3TB of GitHub data covering 48 programming languages. We selected a small portion of this dataset to optimize smaller language models for Ruby, a popular statically typed language.
Target Language: Ruby
Dataset Size:
Training: 900,000 files
Validation: 50,000 files
Test: 50,000 files
Preprocessing:
Selected Ruby as the target language due to its… See the full description on the dataset page: https://huggingface.co/datasets/ammarnasr/the-stack-ruby-clean.gnn-ruby-code-study
GNN Ruby Code Study
Systematic study of Graph Neural Network architectures for Ruby code complexity prediction and generation.
Paper: Graph Neural Networks for Ruby Code Complexity Prediction and Generation: A Systematic Architecture Study
Dataset
22,452 Ruby methods parsed into AST graphs with 74-dimensional node features.
Split
Samples
File
Train
19,084
dataset/train.jsonl
Validation
3,368
dataset/val.jsonl
Each JSONL record contains:
repo_name:… See the full description on the dataset page: https://huggingface.co/datasets/timlawrenz/gnn-ruby-code-study.ruby-code-instructions-80k
Ruby Code Instructions - 80K
Instruction-tuning dataset of Ruby functions or methods paired with short natural-language instructions derived from repository docstrings or inline comments.
What changed in this release
This release keeps the original public rows and format, but makes the dataset easier to use responsibly:
exact duplicate rows were removed again using normalized instruction + output hashing
deterministic train, validation, and test splits were added
the… See the full description on the dataset page: https://huggingface.co/datasets/NickIBrody/ruby-code-instructions-80k.smollm3-stack-v2-RubyRuby-Code-Large
Ruby-Code-Large
Ruby-Code-Large is a large-scale corpus of Ruby programming language source code comprising 331,743 code samples stored in .jsonl format. The dataset is designed to support research and development in large language model (LLM) pretraining, static analysis, web application development, and software engineering automation within the Ruby ecosystem.
By offering a substantial, language-focused dataset, Ruby-Code-Large enables targeted experimentation in dynamic… See the full description on the dataset page: https://huggingface.co/datasets/ajibawa-2023/Ruby-Code-Large.instructional_code-search-net-ruby
Dataset Card for "instructional_code-search-net-ruby"
Dataset Summary
This is an instructional dataset for Ruby.
The dataset contains two different kind of tasks:
Given a piece of code generate a description of what it does.
Given a description generate a piece of code that fulfils the description.
Languages
The dataset is in English.
Data Splits
There are no splits.
Dataset Creation
May of 2023
Curation Rationale
This dataset… See the full description on the dataset page: https://huggingface.co/datasets/Nan-Do/instructional_code-search-net-ruby.spider_dbCodeSearchNet-ccr-ruby-qrelsEmploying the CoIR evaluation framework's dataset version, utilize the code below for assessment:
import coir
from coir.data_loader import get_tasks
from coir.evaluation import COIR
from coir.models import YourCustomDEModel
model_name = "intfloat/e5-base-v2"
# Load the model
model = YourCustomDEModel(model_name=model_name)
# Get tasks
#all task ["codetrans-dl","stackoverflow-qa","apps","codefeedback-mt","codefeedback-st","codetrans-contest","synthetic-
# text2sql","cosqa","codesearchnet"… See the full description on the dataset page: https://huggingface.co/datasets/CoIR-Retrieval/CodeSearchNet-ccr-ruby-qrels.CodeSearchNet-ccr-ruby-queries-corpus
Dataset Card for "CodeSearchNet-ccr-ruby-queries-corpus"
More Information needed
clinicaltrials-completed-phase3
clinicaltrials-completed-phase3-full — Data Card
Version: 1.1.0 | Generated: 2026-06-14T06:18:47.568731+00:00 | Records: 29,633
Dataset Summary
clinicaltrials-completed-phase3-full contains structured clinical trial records from ClinicalTrials.gov, the U.S. federal registry of clinical studies operated by the National Library of Medicine (NIH). Each record includes trial status, design parameters, eligibility criteria, sponsor information, enrollment counts, and… See the full description on the dataset page: https://huggingface.co/datasets/RubyIntelligence/clinicaltrials-completed-phase3.details_Yuma42__KangalKhan-Ruby-7B-Fixed
Dataset Card for Evaluation run of Yuma42/KangalKhan-Ruby-7B-Fixed
Dataset automatically created during the evaluation run of model Yuma42/KangalKhan-Ruby-7B-Fixed on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_Yuma42__KangalKhan-Ruby-7B-Fixed.agriculture-image-depth-clean
Agriculture Image Depth Data Notes
Dataset summary
Preparation notes and schema examples for Agriculture tasks using Image Depth data. Full source material is intentionally not bundled, so provenance and licensing remain explicit.
Included material
load_data.py — loading, cleaning, and split preparation code.
dataset_infos.json — schema and split metadata.
metadata_sample.jsonl — small, human-readable records for checking the schema.
README.md —… See the full description on the dataset page: https://huggingface.co/datasets/rubymkes/agriculture-image-depth-clean.llm-redteam-corpus-taxonomy-core
LLM Red-Team Corpus + Taxonomy — Core
44,681 prompts for red-teaming and safety-testing LLMs. We collected them
from 9 public sources, checked every license, masked personal data, and saved
where each prompt came from. Load it in one line.
Use one clean dataset instead of downloading and fixing 9 red-team benchmarks by
hand. Every prompt keeps its source, license, and citation. The
core tier is safe to use in commercial products — every source is verified
MIT / Apache-2.0 /… See the full description on the dataset page: https://huggingface.co/datasets/RUBYGLASK/llm-redteam-corpus-taxonomy-core.RubyCraft-3.4-Instruct
RubyCraft-3.4-Instruct
RubyCraft-3.4-Instruct is a synthetically generated and rigorously filtered dataset designed to rapidly adapt Small Language Models (SLMs) to the latest programming language specifications, specifically Ruby 3.4.
This dataset demonstrates how high-performance code specialist models can be created at a negligible cost (approximately €4.20), effectively eliminating dependency on expensive, monolithic LLM APIs.
📊 Dataset Summary
The dataset is… See the full description on the dataset page: https://huggingface.co/datasets/mehmetdavut/RubyCraft-3.4-Instruct.wildlife-collection4
Wildlife Multimodal3 Data Notes
Dataset summary
This repository contains a preparation pipeline and a small metadata sample for Wildlife work with Multimodal3 inputs. It does not claim to be a complete benchmark release; the loader documents how source data is normalized and validated.
Included material
clean.py — loading, cleaning, and split preparation code.
dataset_infos.json — schema and split metadata.
metadata_sample.jsonl — small… See the full description on the dataset page: https://huggingface.co/datasets/rubywhite2002/wildlife-collection4.