datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
code_generation
LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code
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💻 GitHub Repository •
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LiveCodeBench is a "live" updating benchmark for holistically evaluating code related capabilities of LLMs.
Particularly, it evaluates LLMs across a range of capabilties including code generation, self-repair, test output prediction, and code execution.
This is the code generation scenario of LiveCodeBench. It is also… See the full description on the dataset page: https://huggingface.co/datasets/livecodebench/code_generation.text-code-galeras-code-generation-from-docstring-3k-dedupedLiveCodeBench-CodeGenerationleetcode_code_generationsynthetic-code-generationsThis dataset was synthetically generated using mixtral8x7b to create unique instructions following the MagicCoder Paper and reproducing the results by modifying specific attributes (snippets are larger, instructions/responses are larger, and more specific).
Below is the prompt used to generate the instruction set:
prompt=f"""<s>[INST] You are an incredibly intelligent programming AI with expertise in CloudFormation, Terraform, AWS CDK and {lang}. Please gain inspiration from the following… See the full description on the dataset page: https://huggingface.co/datasets/VishaalY/synthetic-code-generations.code-generation-sft-100k
Code Generation SFT (100K)
100,000 ShareGPT conversations covering code generation across 8 programming languages, 21 categories, and 22 distinct programming tasks. Each example includes a detailed natural language request and a complete, working implementation with explanations of key design decisions.
Motivation
Coding assistants are the highest-adoption LLM application category, but most open training datasets focus on isolated functions without context. This… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/code-generation-sft-100k.arch-code-transfer-lpi-260903T0846-w2-raw-generationsdeckergui-code-generation
Code generation and reasoning pairs from DeckerGUI development sessions. Contains user instructions, context, and model-generated code for TypeScript, Markdown, and JSON.
Dataset Details
Repository: ctaxnagomi/deckergui-code-generation
License: MIT
DeckerGUI Version: v2.0.0
Created: 2026-08-17
Dataset Schema
See metadata.json for the full schema definition.
Usage
from datasets import load_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/ctaxnagomi/deckergui-code-generation.Code-Generation-LLM-LoRAcode-text-galeras-commit-generation-3k-dedupedLLM-ABAP-Code-Generation-Benchmark
LLM Benchmark ABAP Code Generation Dataset
This dataset is designed for benchmarking Large Language Models (LLMs) on ABAP code generation capabilities. It is based on the HumanEval benchmark, adapted for ABAP, and includes 16 additional ABAP-specific tasks that require interaction with database tables.
Total tasks: 180
164 tasks adapted from HumanEval
16 ABAP-specific tasks
Dataset Structure
dataset.jsonl: Contains 180 examples. Each example has:
id: Unique… See the full description on the dataset page: https://huggingface.co/datasets/timkoehne/LLM-ABAP-Code-Generation-Benchmark.code_generation_ko
code_generation_ko
https://huggingface.co/datasets/livecodebench/code_generation
gpt-4o를 이용해 question_title과 question_content를 한글로 번역한 코딩 질문 데이터셋.
구조
{
"question_title": "분리된 점심",
"question_content": "KEYENCE 본사에 점점 더 많은 직원들이 생기면서, 본사 내 부서들을 두 그룹으로 나누어 점심시간을 시차제로 하기로 결정했습니다.\nKEYENCE 본사에는 N개의 부서가 있으며, i번째 부서(1\\leq i\\leq N)의 인원수는 K_i입니다.\n각 부서를 그룹 A 또는 그룹 B에 배정하고, 각 그룹이 같은 시간에 점심시간을 가지며, 그룹 A와 그룹 B의 점심시간이 겹치지 않도록 할 때, 동시에 점심을 먹는 최대 인원의 최소 가능한 값을 찾으세요.\n즉, 다음 중 더 큰 값의… See the full description on the dataset page: https://huggingface.co/datasets/twodigit/code_generation_ko.code_generation
code_generation
https://huggingface.co/datasets/livecodebench/code_generation
영문 코딩 질문 답변 데이터셋.
구조
{
"question_title": "Separated Lunch",
"question_content": "As KEYENCE headquarters have more and more workers, they decided to divide the departments in the headquarters into two groups and stagger their lunch breaks.\nKEYENCE headquarters have N departments, and the number of people in the i-th department (1\\leq i\\leq N) is K_i.\nWhen assigning each department to… See the full description on the dataset page: https://huggingface.co/datasets/twodigit/code_generation.code-generation-eval
Code Generation Evaluation
5 code generation tasks for evaluating dispatchAI coder models.
Best models: Qwen2.5-0.5B-Coder-mobile, Qwen2.5-Coder-1.5B-mobile
🚀 dispatchAI
lcb_codegeneration_v6_shortradon-test-code_generation
radon-test-code_generation
Description
Code generation test dataset for RADON model evaluation with programming prompts
Usage
Load Dataset
from datasets import load_dataset
dataset = load_dataset("MagistrTheOne/radon-test-code_generation")
print(dataset)
Use with RADON Model
from transformers import AutoModelForCausalLM, AutoTokenizer
# Load RADON model
model = AutoModelForCausalLM.from_pretrained("MagistrTheOne/RadonSAI")
tokenizer =… See the full description on the dataset page: https://huggingface.co/datasets/MagistrTheOne/radon-test-code_generation.code_generation_v2
LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code
🏠 Home Page •
💻 GitHub Repository •
🏆 Leaderboard •
LiveCodeBench is a "live" updating benchmark for holistically evaluating code related capabilities of LLMs.
Particularly, it evaluates LLMs across a range of capabilties including code generation, self-repair, test output prediction, and code execution.
This is the code generation scenario of LiveCodeBench. It is… See the full description on the dataset page: https://huggingface.co/datasets/mathewmouchamel/code_generation_v2.