datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
da-code-evaluation-resultsdetails_llm-agents__tora-code-7b-v1.0
Dataset Card for Evaluation run of llm-agents/tora-code-7b-v1.0
Dataset Summary
Dataset automatically created during the evaluation run of model llm-agents/tora-code-7b-v1.0 on the Open LLM Leaderboard.
The dataset is composed of 64 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"… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_llm-agents__tora-code-7b-v1.0.details_llm-agents__tora-code-34b-v1.0
Dataset Card for Evaluation run of llm-agents/tora-code-34b-v1.0
Dataset automatically created during the evaluation run of model llm-agents/tora-code-34b-v1.0 on the Open LLM Leaderboard.
The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 3 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_llm-agents__tora-code-34b-v1.0.Tau2-Bench-Airline-With-Code-Agents
Dataset Card for a Code Agent Version of Tau Bench 2 Airline
Dataset Summary
This dataset includes sample traces and associated metadata from multi-turn interactions between an code agent and AI assistant. The dataset is based on the Airline environment from Tau^2 Bench and contains traces from both the original version and a version made at Snorkel AI using code agents to solve the same tasks (indicator in the version field; details below).
Curated by: Snorkel AI… See the full description on the dataset page: https://huggingface.co/datasets/snorkelai/Tau2-Bench-Airline-With-Code-Agents.works_on_my_agent_code
Track B Phase 3 Submission
Team: Works on my agent
This archive contains the runnable submission for Track B Phase 3.
Environment
Python 3.11 is recommended for the inference runner:
python3.11 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install -r requirements.txt
Our local validation environment used Huawei Ascend 910B hardware.
The runner does not require internet access at runtime. It connects only to the local vLLM… See the full description on the dataset page: https://huggingface.co/datasets/jinao/works_on_my_agent_code.agentic_code_dataset_22Dataset: 22 Real Claude Code Sessions
To validate Suffix Decoding's applicability in Agentic Coding scenarios, we collected 22 complete Claude Code session recordings.
Dataset Overview
Metric
Value
Collection date
December 2025
Total sessions
22
Total conversation turns
17,487
Total runtime
50 hours
Total input tokens
6,996,619
Total output tokens
6,094,906
Session Scale Distribution
Statistic
Min
Max
Average
Conversation turns
273… See the full description on the dataset page: https://huggingface.co/datasets/novita/agentic_code_dataset_22.Tau2-Bench-Verified-Airline-With-Code-Agents
Dataset Card for a Code Agent Version of Tau Bench 2 Airline
Dataset Summary
This dataset includes sample traces and associated metadata from multi-turn interactions between an code agent and AI assistant, along with the original verion of the tasks with more bespoke tools.
The dataset is based on a verified version of the Airline environment from Sierra.ai's Tau^2 Bench with the verified version from Amazon AGI group here.
You can find an earlier version of the dataset… See the full description on the dataset page: https://huggingface.co/datasets/snorkelai/Tau2-Bench-Verified-Airline-With-Code-Agents.codeagent-pythonagent-code-rl-artifacts
Agent Code RL Artifacts
Recovered process data from a code-generation Agent project covering SFT,
Monte Carlo rollout, process reward modeling, and veRL GRPO. This repository
contains benchmark-derived records and AI-generated content; it is not a
human-authored-only dataset.
Related SFT adapter:
keryszhan/qwen2.5-coder-7b-code-plan-sft.
Data stages
Config
Purpose
Important boundary
splits
Canonical HumanEval/MBPP-derived task splits
grpo_evaluation is… See the full description on the dataset page: https://huggingface.co/datasets/keryszhan/agent-code-rl-artifacts.Code-Gen-Agents-0925
Code Generation Agent Network
A comprehensive collection of specialized AI agents for code generation, development workflows, and project management. While originally designed for Claude Code, these agent specifications are framework-agnostic and can be adapted to work with any AI code generation platform or multi-agent system.
Framework Agnostic Design
This repository contains agent specifications that define:
Clear role definitions and capabilities
Tool requirements… See the full description on the dataset page: https://huggingface.co/datasets/danielrosehill/Code-Gen-Agents-0925.codeagent-tracescontext-primitive-code-agent-pack-v0
Context Primitive Code-Agent Pack v0 — Free Funnel
Free product-specific instruction / Q&A seed material from Primitive Origins’ Context Primitive / Foundry tests.
This is a marketing / companion corpus for the Context Primitive stack — not a general public code-agent marketplace hero SKU.
What’s inside
JSONL splits under data/:
behavior_qa.train.jsonl / .eval.jsonl
instruction_test_generation.train.jsonl / .eval.jsonl
foundry/python_test_generation.*… See the full description on the dataset page: https://huggingface.co/datasets/Primitive-Origins/context-primitive-code-agent-pack-v0.AFM-CodeAgent-SFT-Dataset
Data Introduction
This dataset serves as the core training data for Agent Foundation Models (AFMs), specifically designed to elicit end-to-end multi-agent reasoning capabilities in large language models. Built on the novel "Chain-of-Agents (CoA)" paradigm, the dataset leverages a multi-agent distillation framework to transform collaboration processes from state-of-the-art multi-agent systems into trajectory data suitable for supervised fine-tuning (SFT), simulating dynamic… See the full description on the dataset page: https://huggingface.co/datasets/PersonalAILab/AFM-CodeAgent-SFT-Dataset.ai-code-generation-swe-agents-2026
💻 AI Code Generation, SWE Agents & Program Synthesis Dataset (2026 Edition)
A structured research dataset featuring 3,181 domain-verified research papers and 771 official code repositories focused on Autonomous Software Engineering Agents (SWE-bench), Program Synthesis, DeepSeek-Coder-V2, Qwen2.5-Coder, Test-Driven Code Repair, Self-Healing Software, AST Semantic Modeling, and Formal Logic Verification (2023–2026).
Built with Universal Scientific Engine V17.1 Gold, providing 47… See the full description on the dataset page: https://huggingface.co/datasets/beatsprom/ai-code-generation-swe-agents-2026.agentic-code
Unified Agentic Coding CoT Dataset
This dataset is a curated fusion of high-quality agentic coding trajectories, specifically optimized for fine-tuning small, high-performance models like Qwen2.5-Coder-0.5B-Instruct. It combines systematic reasoning (Chain-of-Thought) with practical tool-use and code editing capabilities.
Dataset Summary
The dataset unifies two primary sources into a single, instruction-following format:… See the full description on the dataset page: https://huggingface.co/datasets/FlameF0X/agentic-code.engosoft-local-code-agent-eval
Engosoft — Local Code Agent: Eval Harness & Findings
Golden-set eval harness and measured findings for building a local coding agent
on Apple Silicon (M5 Pro, 24GB), targeting frontend/backend web work with Arabic
(Egyptian) as a first-class language.
Base model evaluated: mlx-community/Qwen3-Coder-30B-A3B-Instruct-4bit
(30.5B MoE, 3B active, 16.0 GiB at 4-bit).
Headline finding
Injecting a design-system document as a system prompt makes this model worse —… See the full description on the dataset page: https://huggingface.co/datasets/Escanor77/engosoft-local-code-agent-eval.hermes-function-calling-v1-formatted-code-agentEpistemeAI__Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.003-128K-code-ds-auto-details
Dataset Card for Evaluation run of EpistemeAI/Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.003-128K-code-ds-auto
Dataset automatically created during the evaluation run of model EpistemeAI/Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.003-128K-code-ds-auto
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 5 run(s). Each run can be found as a specific split in each configuration, the split being named… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/EpistemeAI__Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.003-128K-code-ds-auto-details.synthetic-code-agent-trajectories
For buyers
To purchase the full dataset, contact me via telegram.
@HecklerKoch416C
Synthetic Code Agent Trajectories (Sample)
125 synthetic agent trajectories for training and evaluating code agents in a Python sandbox.
Each trajectory is a complete, multi-step interaction where an AI agent solves a programming task using real tools: writing files, reading them, executing Python code in an isolated sandbox, and observing the actual output.
What's… See the full description on the dataset page: https://huggingface.co/datasets/Jurgen1161/synthetic-code-agent-trajectories.misc-merged-claude-code-traces-v1
MISC Unification of Public Claude Code Traces
A unified dataset of 32,133 deduplicated Claude API conversation traces focused on software engineering and code generation tasks. This dataset merges and normalizes traces from 10 different source datasets into a single, consistent format.
Dataset Description
This dataset contains real Claude API interaction traces capturing software engineering workflows including:
Code generation and modification
Bug fixing and… See the full description on the dataset page: https://huggingface.co/datasets/agent-data/misc-merged-claude-code-traces-v1.agent-traces-code-review-pipeline
Agent Traces: code-review-pipeline
Synthetic multi-agent workflow traces with LLM-enriched content for the code-review-pipeline domain.
Part of the juliensimon/open-agent-traces collection — 10 datasets covering diverse domains and workflow patterns.
What is this dataset?
This dataset contains 2,035 events across 50 workflow runs, each representing a complete multi-agent execution trace. Every trace includes:
Agent reasoning — chain-of-thought for each agent step
LLM… See the full description on the dataset page: https://huggingface.co/datasets/juliensimon/agent-traces-code-review-pipeline.hermes-codeagentEpistemeAI2__Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.005-128K-code-COT-details
Dataset Card for Evaluation run of EpistemeAI2/Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.005-128K-code-COT
Dataset automatically created during the evaluation run of model EpistemeAI2/Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.005-128K-code-COT
The dataset is composed of 38 configuration(s), each one corresponding 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/EpistemeAI2__Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.005-128K-code-COT-details.AFM-CodeAgent-RL-Dataset
Data Introduction
This dataset serves as the core training data for Agent Foundation Models (AFMs), specifically designed to elicit end-to-end multi-agent reasoning capabilities in large language models. Built on the novel "Chain-of-Agents (CoA)" paradigm, the dataset leverages a multi-agent distillation framework to transform collaboration processes from state-of-the-art multi-agent systems into trajectory data suitable for supervised fine-tuning (SFT), simulating dynamic… See the full description on the dataset page: https://huggingface.co/datasets/PersonalAILab/AFM-CodeAgent-RL-Dataset.details_llm-agents__tora-code-13b-v1.0
Dataset Card for Evaluation run of llm-agents/tora-code-13b-v1.0
Dataset automatically created during the evaluation run of model llm-agents/tora-code-13b-v1.0 on the Open LLM Leaderboard.
The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 3 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_llm-agents__tora-code-13b-v1.0.EpistemeAI__Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.004-128K-code-COT-details
Dataset Card for Evaluation run of EpistemeAI/Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.004-128K-code-COT
Dataset automatically created during the evaluation run of model EpistemeAI/Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.004-128K-code-COT
The dataset is composed of 38 configuration(s), each one corresponding 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/EpistemeAI__Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.004-128K-code-COT-details.agentic-code-search-rollouts-sample10EpistemeAI__Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.003-128K-code-details
Dataset Card for Evaluation run of EpistemeAI/Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.003-128K-code
Dataset automatically created during the evaluation run of model EpistemeAI/Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.003-128K-code
The dataset is composed of 38 configuration(s), each one corresponding 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/EpistemeAI__Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.003-128K-code-details.EpistemeAI__Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.004-128K-code-ds-auto-details
Dataset Card for Evaluation run of EpistemeAI/Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.004-128K-code-ds-auto
Dataset automatically created during the evaluation run of model EpistemeAI/Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.004-128K-code-ds-auto
The dataset is composed of 38 configuration(s), each one corresponding 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/EpistemeAI__Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.004-128K-code-ds-auto-details.reap-agent-code
reap-agent-code
Dataset Summary
reap-agent-code is a REAP-style mixed dataset for training LLM coding agents.
It is optimized for agentic coding behavior: writing code, debugging, and tool use.
Each row is JSONL with the schema:
{"text": "..."}
Dataset Composition
Source
Ratio
Count
Signal
evol
45%
9 000
Instruction-to-code
swe
25%
5 000
Bug-fix / problem-solving
xlam
30%
6 000Tool / function calling
Total: 20 000 unique deduplicated… See the full description on the dataset page: https://huggingface.co/datasets/freddm/reap-agent-code.