datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
code_contests_instruct
Dataset Card for "code_contests_instruct"
The deepmind/code_contests dataset formatted as markdown-instruct for text generation training.
There are several different configs. Look at them. Comments:
flesch_reading_ease is computed on the description col via textstat
hq means that python2 (aka PYTHON in language column) is dropped, and keeps only rows with flesch_reading_ease 75 or greater
min-cols drops all cols except language and text
possible values for language are {'CPP'… See the full description on the dataset page: https://huggingface.co/datasets/BEE-spoke-data/code_contests_instruct.HelpSteer3-general-code-Shift-Qwen-2.5-1.5B-Instruct-chat-formatted-generationsself-instruct-starcoder
Self-instruct-starcoder
Summary
Self-instruct-starcoder is a dataset that was generated by prompting starcoder to generate new instructions based on some human-written seed instructions.
The underlying process is explained in the paper self-instruct. This algorithm gave birth to famous machine generated
datasets such as Alpaca and Code Alpaca which are two datasets
obtained by prompting OpenAI text-davinci-003 engine.
Our approach
While our method is… See the full description on the dataset page: https://huggingface.co/datasets/codeparrot/self-instruct-starcoder.self-oss-instruct-sc2-exec-filter-prompt-codes-test-50kdistill_r1_code_evol_instructcode_contest_instruct_cppbigcodebench_codellama_codellama-7b-instruct-hf_tokenizedCodeMaster-Phi-Instruct
Code Master Phi is a compiled dataset designed for training Phi3 instruct models. This dataset is focused on code-based data and integrates multiple high-quality sources to ensure a robust training foundation. The sources include:
Replete-AI/code_bagel: A diverse collection of code snippets and examples.
nickrosh/Evol-Instruct-Code-80k-v1: A dataset featuring evolved instructions for code generation tasks.
iamtarun/python_code_instructions_18k_alpaca: A compilation of Python code… See the full description on the dataset page: https://huggingface.co/datasets/thesven/CodeMaster-Phi-Instruct.evol_instruct_code_filtered_39k
Dataset Card for "evol_instruct_code_filtered_38k"
Filtered version of nickrosh/Evol-Instruct-Code-80k-v1, with manual filtering, and automatic filtering based on quality and learning value classifiers.
deepcoder-train-deepcoder-qwen4b-instruct-cont-temp0_6-32k-hsrun_step230-codeonly_truncationtiny-codes-instructBase dataset: iamtarun/code_instructions_120k_alpaca
gemma4-code-review-instruct
gemma4-code-review-instruct
197K code review examples — 58K with chain-of-thought <think> reasoning traces.
Built to train models that don't just flag issues, but explain their reasoning before delivering a review. Drop-in ready for SFT with any chat model.
Why This Dataset
Most code review datasets give you diff → comment. This one gives you diff → think → comment for 30% of examples — reasoning traces that show how to analyze a diff before writing the review.… See the full description on the dataset page: https://huggingface.co/datasets/liodon-ai/gemma4-code-review-instruct.deepcoder-train-Qwen_qwen3-4b-instruct-2507-codeonly_truncationSynthUI-Code-Instruct-2k-v1Synth UI 🎹
https://www.synthui.design
Dataset details
This dataset aims to provide a diverse collection of NextJS code snippets, along with their corresponding instructions, to facilitate the training of language models for NextJS-related tasks. It is designed to cover a wide range of NextJS functionalities, including UI components, routing, state management, and more.
This dataset consists of:
Note: The dataset is seperated into two main parts:
raw Contains only the… See the full description on the dataset page: https://huggingface.co/datasets/JulianAT/SynthUI-Code-Instruct-2k-v1.code-review-instruct-critique-revision
Dataset Card for "code-review-instruct-critique-revision"
More Information needed
CodeChat-Instruct-v1
CodeChat-Instruct-v1
CodeChat-Instruct-v1 is a synthetic coding instruction dataset designed for supervised fine-tuning of language models on programming-related conversations. It includes diverse coding tasks such as code review, code improvement, complexity analysis, edge-case discussion, code explanation, library/API usage, refactoring guidance. The dataset is suitable for training coding assistants, educational programming tutors, and general-purpose code LLMs with strong… See the full description on the dataset page: https://huggingface.co/datasets/kd13/CodeChat-Instruct-v1.instruct_code_search_net
Dataset Card for "instruct_code_search_net"
More Information needed
details_Qwen__Qwen2.5-Coder-14B-Instruct
Dataset Card for Evaluation run of Qwen/Qwen2.5-Coder-14B-Instruct
Dataset automatically created during the evaluation run of model Qwen/Qwen2.5-Coder-14B-Instruct.
The dataset is composed of 136 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 pointing to the latest results.… See the full description on the dataset page: https://huggingface.co/datasets/OALL/details_Qwen__Qwen2.5-Coder-14B-Instruct.deepcoder-test-deepcoder-qwen4b-instruct-cont-temp0_6-32k-hsrun_step230-codeonly_truncationeval-Qwen3-Coder-30B-A3B-Instruct_16concurrency_openhands_eval_c_terminal-bench-2.0code-review-instruct-critique-revision-pythonadaption-code-oss-instruct-raw-aug
OSS-Instruct Coding Tasks (Augmented)
Coding problems inspired by open-source snippets, with solutions across several languages.
Rows
8,996
Domain
programming
Format
data.parquet, one row per example
Licence
other
Built for
supervised fine-tuning (SFT) experiments on Adaption AutoScientist
Columns
Column
Description
original_prompt
The prompt (user turn) as uploaded.
original_completion
The target response as uploaded.… See the full description on the dataset page: https://huggingface.co/datasets/rodriguescarson/adaption-code-oss-instruct-raw-aug.adaption-code-oss-instruct-raw
OSS-Instruct Coding Tasks
Coding problems inspired by open-source snippets, with solutions across several languages.
Rows
3,000
Domain
programming
Format
data.parquet, one row per example
Licence
mit
Built for
supervised fine-tuning (SFT) experiments on Adaption AutoScientist
Columns
Column
Description
original_prompt
The prompt (user turn) as uploaded.
original_completion
The target response as uploaded.
enhanced_prompt… See the full description on the dataset page: https://huggingface.co/datasets/rodriguescarson/adaption-code-oss-instruct-raw.adaption-code-oss-instruct-raw-aug-e5bca4
OSS-Instruct Coding Tasks (Augmented)
Coding problems inspired by open-source snippets, with solutions across several languages.
Rows
7,000
Domain
programming
Format
data.parquet, one row per example
Licence
other
Built for
supervised fine-tuning (SFT) experiments on Adaption AutoScientist
Columns
Column
Description
original_prompt
The prompt (user turn) as uploaded.
original_completion
The target response as uploaded.… See the full description on the dataset page: https://huggingface.co/datasets/rodriguescarson/adaption-code-oss-instruct-raw-aug-e5bca4.Instruct-Python-Code-Turkish
Dataset Card for Instruct-Python-Code-Turkish
Language: Turkish
Dataset Description
The translation was performed using the Google translation model to ensure high-quality, accurate translation.
Dataset Details
Size: ≈5K
Translation tool: Google Translate
Data format: Instruct, Output
communityai_apt-instruct-code-micro-600keval-Qwen3-Coder-30B-A3B-Instruct_terminal-bench-2.0Evol-Instruct-Code-80k-v1-rogery-2k-sampled-20250426a1_code_star_coder_instruct_eval_636d
mlfoundations-dev/a1_code_star_coder_instruct_eval_636d
Precomputed model outputs for evaluation.
Evaluation Results
Summary
Metric
AIME24
AMC23
MATH500
MMLUPro
JEEBench
GPQADiamond
LiveCodeBench
CodeElo
CodeForces
Accuracy
15.0
51.0
72.2
28.2
34.2
35.9
29.0
6.9
5.3
AIME24
Average Accuracy: 15.00% ± 0.85%
Number of Runs: 10
Run
Accuracy
Questions Solved
Total Questions
1
13.33%
4
30
2
13.33%
4
30
3
16.67%
5
30
4… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-dev/a1_code_star_coder_instruct_eval_636d.code-instruct-mixed
Description
Filtered/normalised subsets of public code-instruction datasets (Magicoder OSS-Instruct & Evol-Instruct, CodeFeedback, Glaive). The source column attributes each row to its origin; each source retains its upstream licence.
Derived dataset. Source material retains its original per-item licence (see source/repo columns); treat as other / mixed. Provided as-is.
Usage
from datasets import load_dataset
ds = load_dataset("PotatoHD/code-instruct-mixed")