datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
gpt-5.6-sol-coding-and-debugging-traces
GPT-5.6 Sol Coding & Debugging Traces
Verified software-engineering, independent model-judging, seed-authoring,
defensive-security, and training-harness trajectories from
GPT-5.6 Sol (gpt-5.6-sol) running through the Codex CLI as an
autonomous coding agent. Sessions show the observable development loop:
inspecting repositories, reproducing failures, explaining evidence, editing
files, running compilers and test suites, correcting mistakes, and verifying
the completed result.… See the full description on the dataset page: https://huggingface.co/datasets/greghavens/gpt-5.6-sol-coding-and-debugging-traces.code-debugging-sft-50k
Code Debugging SFT (50K)
50,000 ShareGPT-format conversations where the user presents buggy code and the assistant provides root-cause analysis and a corrected solution. Covers Python, JavaScript, Go, TypeScript, and SQL across 14 bug categories.
Motivation
Debugging is one of the most frequent developer tasks — and one of the hardest to train. Most coding datasets focus on writing code from scratch. This dataset trains models to:
Identify the precise root cause… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/code-debugging-sft-50k.nemotron-terminal-debugging
nemotron-terminal-debugging
Per-source partition of nvidia/Nemotron-Terminal-Corpus,
filtered to source == "debugging". The difficulty column preserves the original
easy / medium / mixed split (na for the dataset_adapters/* files, which
did not carry a difficulty label).
Partitioning scheme:
adapters_{code,math,swe} — rows from dataset_adapters/{code,math,swe}.parquet
{skill} (e.g. debugging, security, …) — rows from
synthetic_tasks/skill_based/{easy,medium… See the full description on the dataset page: https://huggingface.co/datasets/laion/nemotron-terminal-debugging.gpt-5.6-sol-coding-and-debugging-traces
GPT-5.6 Sol Coding & Debugging Traces
Verified software-engineering, independent model-judging, seed-authoring,
defensive-security, and training-harness trajectories from
GPT-5.6 Sol (gpt-5.6-sol) running through the Codex CLI as an
autonomous coding agent. Sessions show the observable development loop:
inspecting repositories, reproducing failures, explaining evidence, editing
files, running compilers and test suites, correcting mistakes, and verifying
the completed result.… See the full description on the dataset page: https://huggingface.co/datasets/11-47/gpt-5.6-sol-coding-and-debugging-traces.python_debugging
Python Debugging
A synthetic instruction-tuning dataset for training AI models to identify and fix bugs in Python code.
Dataset Summary
Field
Value
Entries
75
Format
input / output pairs
Language
English
Topic
Finding and fixing bugs in Python code
Synthetic
Yes, generated with DeepSeek
License
MIT
Dataset Description
Each entry presents a snippet of Python code containing a deliberate bug, along with a corrected version… See the full description on the dataset page: https://huggingface.co/datasets/creeperdatasets/python_debugging.gpt-5.6-sol-coding-and-debugging-traces
GPT-5.6 Sol Coding & Debugging Traces
Verified software-engineering, independent model-judging, seed-authoring,
defensive-security, and training-harness trajectories from
GPT-5.6 Sol (gpt-5.6-sol) running through the Codex CLI as an
autonomous coding agent. Sessions show the observable development loop:
inspecting repositories, reproducing failures, explaining evidence, editing
files, running compilers and test suites, correcting mistakes, and verifying
the completed result.… See the full description on the dataset page: https://huggingface.co/datasets/ArkhAngelLifeJiggy/gpt-5.6-sol-coding-and-debugging-traces.AI-Agent-Generating-Tool-Debugging-Prompt-Library
Dataset Card for "AI Agent Generating Tool & Debugging Prompt Library" 🤖⚙️
Dataset Details 📚
Dataset Name: AI Agent Generating Tool & Debugging Prompt Library
Dataset Description:This dataset includes a collection of prompts focused on building and debugging AI-driven tools, including creating self-improving AI agents and debugging prompts for Python projects. The dataset is designed for use in fine-tuning models related to code generation, debugging, and software… See the full description on the dataset page: https://huggingface.co/datasets/Chemically-motivated/AI-Agent-Generating-Tool-Debugging-Prompt-Library.gpt-5.6-sol-coding-and-debugging-traces
GPT-5.6 Sol Coding & Debugging Traces
Verified software-engineering, independent model-judging, seed-authoring,
defensive-security, and training-harness trajectories from
GPT-5.6 Sol (gpt-5.6-sol) running through the Codex CLI as an
autonomous coding agent. Sessions show the observable development loop:
inspecting repositories, reproducing failures, explaining evidence, editing
files, running compilers and test suites, correcting mistakes, and verifying
the completed result.… See the full description on the dataset page: https://huggingface.co/datasets/Manusagents/gpt-5.6-sol-coding-and-debugging-traces.gpt-5.6-sol-coding-and-debugging-traces
GPT-5.6 Sol Coding & Debugging Traces
Verified software-engineering, independent model-judging, seed-authoring,
defensive-security, and training-harness trajectories from
GPT-5.6 Sol (gpt-5.6-sol) running through the Codex CLI as an
autonomous coding agent. Sessions show the observable development loop:
inspecting repositories, reproducing failures, explaining evidence, editing
files, running compilers and test suites, correcting mistakes, and verifying
the completed result.… See the full description on the dataset page: https://huggingface.co/datasets/Nobody05/gpt-5.6-sol-coding-and-debugging-traces.