datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Omni-Frontier-Distillation-SFT-Cyber-Coding-Med-dataset-collection
🧬 Omni-Frontier Collection
Cybersecurity · Coding · Math · Science · RSI Reasoning — one unified SFT package
A unified, deduplicated, fully-browsable distillation & SFT corpus — every row real, every row visible.
📖 Jump to
What's inside · 🔁 Aggregation audit · 🛡 Cybersecurity · 💻 Coding · 🏭 Distillation deep-dive · 🔁 RSI · 🧮 Math/Science/More · 🎓 Training guide · 🔎 Browsing · 🧹 Quality · 🗺 Roadmap · 📄 License… See the full description on the dataset page: https://huggingface.co/datasets/SHSLab/Omni-Frontier-Distillation-SFT-Cyber-Coding-Med-dataset-collection.fable-5-coding-and-debugging-traces
Claude Fable 5 Agent Traces
2,380 TRAJECTORIES · 12,490 TRAINING ROWS · 14 MB PARQUET · 663 MB JSONL
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Behavior-preserving instruction-following, tool-use, and agent trajectories
from Claude Fable 5 (anthropic/claude-fable-5). The category and row-share tables
below describe the actual mix seen during training rather than assuming a
particular task… See the full description on the dataset page: https://huggingface.co/datasets/DSFFGFG456/fable-5-coding-and-debugging-traces.kimi-k3-coding-and-debugging-traces
Kimi K3 Coding, Tool Use & Instruction Following Traces
582 TRAJECTORIES · 3,956 TRAINING ROWS · 3 MB PARQUET · 72 MB JSONL
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Behavior-preserving instruction-following, tool-use, and agent trajectories
from Kimi K3 (moonshotai/kimi-k3). The category and row-share tables
below describe the actual mix seen during training rather than assuming a… See the full description on the dataset page: https://huggingface.co/datasets/greghavens/kimi-k3-coding-and-debugging-traces.glm-5.2-coding-and-debugging-traces
GLM 5.2 Agent Traces
207 TRAJECTORIES · 1,821 TRAINING ROWS · 1 MB PARQUET · 35 MB JSONL
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Behavior-preserving instruction-following, tool-use, and agent trajectories
from GLM 5.2 (glm-5.2). The category and row-share tables
below describe the actual mix seen during training rather than assuming a
particular task domain.
This is an actively growing… See the full description on the dataset page: https://huggingface.co/datasets/greghavens/glm-5.2-coding-and-debugging-traces.Omni-Frontier-Distillation-SFT-Cyber-security-Coding-dataset-collection-v2
🧬 Omni-Frontier Collection
Cybersecurity · Coding · Math · Science · RSI Reasoning — one unified SFT package
A unified, deduplicated, fully-browsable distillation & SFT corpus — every row real, every row visible.
📖 Jump to
What's inside · 🔁 Aggregation audit · 🛡 Cybersecurity · 💻 Coding · 🏭 Distillation deep-dive · 🔁 RSI · 🧮 Math/Science/More · 🎓 Training guide · 🔎 Browsing · 🧹 Quality · 🗺 Roadmap · 📄 License… See the full description on the dataset page: https://huggingface.co/datasets/Manusagents/Omni-Frontier-Distillation-SFT-Cyber-security-Coding-dataset-collection-v2.SI2CA-Training-TrajectoriesDataset Card for SI2CA-Training-Trajectories
[🌐 Website] •
[🤗 Dataset] •
[📜 Paper] •
[🐱 GitHub]
💡 Introduction
This dataset consists of 32,340 coding-agent trajectories generated by Qwen3.5-122B-A10B on the same 10,780 executable Python SWE tasks under the three trajectory-curation settings of Section 4.4 of the paper: standard sampling, full self-judgement, and an efficient discovered strategy found by the recursive self-improvement framework. Each task is… See the full description on the dataset page: https://huggingface.co/datasets/Self-Improving-Coding-Agents/SI2CA-Training-Trajectories.kimi-k3-coding-and-debugging-traces
Kimi K3 Coding, Tool Use & Instruction Following Traces
582 TRAJECTORIES · 3,956 TRAINING ROWS · 3 MB PARQUET · 72 MB JSONL
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Behavior-preserving instruction-following, tool-use, and agent trajectories
from Kimi K3 (moonshotai/kimi-k3). The category and row-share tables
below describe the actual mix seen during training rather than assuming a… See the full description on the dataset page: https://huggingface.co/datasets/11-47/kimi-k3-coding-and-debugging-traces.guidellm-agentic-coding-trajectories
GuideLLM agentic coding trajectories
A sampled serving-load benchmark derived from Thoughtworks agentic-coding-trajectories, for GuideLLM and an OpenAI-compatible /v1/chat/completions endpoint. There are 630 rows representing 481 unique source sessions, across the same 8turn, 24turn, and 48turn configurations as the earlier version.
The configuration names now refer to original logical steps, not always HTTP request counts. Native tool steps expand into a tool-call request and a… See the full description on the dataset page: https://huggingface.co/datasets/zetomatoz/guidellm-agentic-coding-trajectories.agentic-coding-trajectories
agentic-coding-trajectories
A unified, tokenized corpus of 15,000 multi-turn agentic-coding sessions (618K turns, 41 turns/session avg) drawn from three publicly-released upstream datasets. Built for benchmarking LLM serving systems on realistic multi-turn coding-agent workloads.
Why this exists
Most LLM serving benchmarks use single-shot prompts. Real coding agents work in long multi-turn loops where each turn appends to a growing prompt. This corpus captures that shape… See the full description on the dataset page: https://huggingface.co/datasets/thoughtworks/agentic-coding-trajectories.glm-5.2-coding-and-debugging-traces
GLM 5.2 Agent Traces
207 TRAJECTORIES · 1,821 TRAINING ROWS · 1 MB PARQUET · 35 MB JSONL
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Behavior-preserving instruction-following, tool-use, and agent trajectories
from GLM 5.2 (glm-5.2). The category and row-share tables
below describe the actual mix seen during training rather than assuming a
particular task domain.
This is an actively growing… See the full description on the dataset page: https://huggingface.co/datasets/11-47/glm-5.2-coding-and-debugging-traces.Synthetic-JP-EN-Coding-Dataset-801k
Synthetic-JP-EN-Coding-Dataset-801k
Magpieによって作成したコードSFTデータセットであるAratako/Synthetic-JP-EN-Coding-Dataset-Magpie-69kを元に、Evol-Instructのような手法を用いて複数のinstructionとresonseを生成し拡張して作成した、日英混合801262件のコードSFT用合成データセットです。
日本語: 173849件
英語: 627413件
元のinstructionの作成に利用したモデルは以下の通りです。modelキーに該当レコードの作成に利用したモデル情報があります。
nvidia/Nemotron-4-340B-Instruct
microsoft/Phi-3-medium-4k-instruct
mistralai/Mixtral-8x22B-Instruct-v0.1… See the full description on the dataset page: https://huggingface.co/datasets/Aratako/Synthetic-JP-EN-Coding-Dataset-801k.kimi-k3-coding-and-debugging-traces
Kimi K3 Coding, Tool Use & Instruction Following Traces
697 TRAJECTORIES · 4,890 TRAINING ROWS · 3 MB PARQUET · 89 MB JSONL
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Behavior-preserving instruction-following, tool-use, and agent trajectories
from Kimi K3 (moonshotai/kimi-k3). The category and row-share tables
below describe the actual mix seen during training rather than assuming a… See the full description on the dataset page: https://huggingface.co/datasets/jiajiale9/kimi-k3-coding-and-debugging-traces.glm-5.2-coding-and-debugging-traces
GLM 5.2 Agent Traces
207 TRAJECTORIES · 1,821 TRAINING ROWS · 1 MB PARQUET · 35 MB JSONL
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Behavior-preserving instruction-following, tool-use, and agent trajectories
from GLM 5.2 (glm-5.2). The category and row-share tables
below describe the actual mix seen during training rather than assuming a
particular task domain.
This is an actively growing… See the full description on the dataset page: https://huggingface.co/datasets/rashdan1/glm-5.2-coding-and-debugging-traces.fable-5-coding-and-debugging-traces-synthetic-corrections
Model Synthetic Corrections
1 TRAJECTORIES · 2 TRAINING ROWS · 16 kB
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Synthetic Corrections companion dataset. The original dataset is greghavens/fable-5-coding-and-debugging-traces. These are narrowly, synthetically corrected, independently re-judged traces that never passed in the original dataset.
Behavior-preserving instruction-following… See the full description on the dataset page: https://huggingface.co/datasets/greghavens/fable-5-coding-and-debugging-traces-synthetic-corrections.fable-5-coding-and-debugging-traces-synthetic
Model Synthetic Corrections
1 TRAJECTORIES · 2 TRAINING ROWS · 16 kB
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Synthetic Corrections companion dataset. The original dataset is greghavens/fable-5-coding-and-debugging-traces. These are narrowly, synthetically corrected, independently re-judged traces that never passed in the original dataset.
Behavior-preserving instruction-following… See the full description on the dataset page: https://huggingface.co/datasets/11-47/fable-5-coding-and-debugging-traces-synthetic.TR-coding-data
TR Coding Data (v0.2)
English | Türkçe
Documents / Doküman: 28
Tokens / Token: 317,427 (Qwen/Qwen3-0.6B tokenizer)
from datasets import load_dataset
ds = load_dataset("TozAI/TR-coding-data", split="train")
English
Raw-text documents that explain programming in Turkish with embedded code,
intended for pretraining / mid-training of language models. Each row is one
self-contained document (tutorial, project walkthrough, debugging session, ...).
How it… See the full description on the dataset page: https://huggingface.co/datasets/TozAI/TR-coding-data.glm-5.2-coding-and-debugging-traces
GLM 5.2 Agent Traces
207 TRAJECTORIES · 1,821 TRAINING ROWS · 1 MB PARQUET · 35 MB JSONL
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Behavior-preserving instruction-following, tool-use, and agent trajectories
from GLM 5.2 (glm-5.2). The category and row-share tables
below describe the actual mix seen during training rather than assuming a
particular task domain.
This is an actively growing… See the full description on the dataset page: https://huggingface.co/datasets/ArkhAngelLifeJiggy/glm-5.2-coding-and-debugging-traces.synthesized-coding-assistant-dataset
Synthesized Coding Assistant Dataset
Overview
Coding assistants are increasingly used for real-world software engineering workflows. However, there are relatively few datasets that closely resemble how such assistants operate in practice.
Many existing coding datasets are based on single-turn or single-iteration tasks, where a model receives one coding request and directly produces an answer or patch. In contrast, practical coding assistants often work through… See the full description on the dataset page: https://huggingface.co/datasets/squeezebits/synthesized-coding-assistant-dataset.fable-5-coding-and-debugging-traces
Claude Fable 5 Agent Traces
2,161 TRAJECTORIES · 11,235 TRAINING ROWS · 11 MB PARQUET · 656 MB JSONL
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Behavior-preserving instruction-following, tool-use, and agent trajectories
from Claude Fable 5 (anthropic/claude-fable-5). The category and row-share tables
below describe the actual mix seen during training rather than assuming a
particular task… See the full description on the dataset page: https://huggingface.co/datasets/ArkhAngelLifeJiggy/fable-5-coding-and-debugging-traces.fable-5-coding-and-debugging-traces
Claude Fable 5 Agent Traces
2,161 TRAJECTORIES · 11,235 TRAINING ROWS · 11 MB PARQUET · 656 MB JSONL
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Behavior-preserving instruction-following, tool-use, and agent trajectories
from Claude Fable 5 (anthropic/claude-fable-5). The category and row-share tables
below describe the actual mix seen during training rather than assuming a
particular task… See the full description on the dataset page: https://huggingface.co/datasets/siddharth0713/fable-5-coding-and-debugging-traces.fable-5-coding-and-debugging-traces
Claude Fable 5 Agent Traces
2,374 TRAJECTORIES · 12,448 TRAINING ROWS · 14 MB PARQUET · 662 MB JSONL
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Behavior-preserving instruction-following, tool-use, and agent trajectories
from Claude Fable 5 (anthropic/claude-fable-5). The category and row-share tables
below describe the actual mix seen during training rather than assuming a
particular task… See the full description on the dataset page: https://huggingface.co/datasets/moehamid/fable-5-coding-and-debugging-traces.local-agentic-coding-bench-8gb-vram-2026-05
agentic coding benchmark: local LLMs on 8GB VRAM
can local LLMs do agentic coding (multi-turn tool calling, file creation, debugging) on consumer hardware? this dataset captures real test results.
hardware
GPU: NVIDIA RTX 4060 Ti 8GB
CPU: Intel i7-14700F
RAM: 32 GB DDR5
OS: Windows 11 + WSL2 (Ubuntu)
inference: llama-server (turboquant fork of llama.cpp)
what was tested
two agent frameworks:
Hermes Agent (NousResearch): structured tool calling with… See the full description on the dataset page: https://huggingface.co/datasets/witcheer/local-agentic-coding-bench-8gb-vram-2026-05.kimi-k3-coding-and-debugging-traces
Kimi K3 Coding, Tool Use & Instruction Following Traces
582 TRAJECTORIES · 3,956 TRAINING ROWS · 3 MB PARQUET · 72 MB JSONL
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Behavior-preserving instruction-following, tool-use, and agent trajectories
from Kimi K3 (moonshotai/kimi-k3). The category and row-share tables
below describe the actual mix seen during training rather than assuming a… See the full description on the dataset page: https://huggingface.co/datasets/Distillio/kimi-k3-coding-and-debugging-traces.kimi-k3-coding-and-debugging-traces
Kimi K3 Coding, Tool Use & Instruction Following Traces
601 TRAJECTORIES · 4,089 TRAINING ROWS · 3 MB PARQUET · 73 MB JSONL
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Behavior-preserving instruction-following, tool-use, and agent trajectories
from Kimi K3 (moonshotai/kimi-k3). The category and row-share tables
below describe the actual mix seen during training rather than assuming a… See the full description on the dataset page: https://huggingface.co/datasets/moehamid/kimi-k3-coding-and-debugging-traces.hf-coding-tools-dashboard
HuggingFace AI Coding Tools Dashboard
Benchmark data from the HuggingFace AI Dashboard — tracking how AI coding tools (Claude Code, Codex, Copilot, Cursor) recommend HuggingFace products across 32 developer categories.
Dataset Structure
Split
Description
Rows
results
Full benchmark results with LLM responses, cost, tokens, latency, and product detection
9146
queries
Benchmark query definitions across 32 categories
404
runs
Run metadata and tool/model… See the full description on the dataset page: https://huggingface.co/datasets/davidkling/hf-coding-tools-dashboard.agentic-coding-traces
Agentic Coding Mooncake Traces
Synthetic agentic coding benchmark datasets in Mooncake trace (JSONL) format,
generated with AIPerf 0.9.0 for LLM inference benchmarking.
Designed for use with InferenceX via the
agentic-replay scenario-type and aiperf_adapter.py.
Files
File
Sessions
Turns
max_prompt_tokens
Seed
64k/dataset.jsonl
1,000
18,595
65,536
42
128k/dataset.jsonl
1,000
16,957
131,072
42
Format
Each line is a Mooncake trace… See the full description on the dataset page: https://huggingface.co/datasets/thangquang09/agentic-coding-traces.hf-coding-tools-dashboard-all
HuggingFace AI Coding Tools Dashboard
Benchmark data from the HuggingFace AI Dashboard — tracking how AI coding tools (Claude Code, Codex, Copilot, Cursor) recommend HuggingFace products across 32 developer categories.
Dataset Structure
Split
Description
Rows
results
Full benchmark results with LLM responses, cost, tokens, latency, and product detection
9603
queries
Benchmark query definitions across 32 categories
404
runs
Run metadata and tool/model… See the full description on the dataset page: https://huggingface.co/datasets/davidkling/hf-coding-tools-dashboard-all.hf-coding-tools-dashboard-builder
HuggingFace AI Coding Tools Dashboard
Benchmark data from the HuggingFace AI Dashboard — tracking how AI coding tools (Claude Code, Codex, Copilot, Cursor) recommend HuggingFace products across 32 developer categories.
Dataset Structure
Split
Description
Rows
results
Full benchmark results with LLM responses, cost, tokens, latency, and product detection
581
queries
Benchmark query definitions across 32 categories
120
runs
Run metadata and tool/model… See the full description on the dataset page: https://huggingface.co/datasets/davidkling/hf-coding-tools-dashboard-builder.hf-coding-tools-dashboard-v2
HuggingFace AI Coding Tools Dashboard (Enhanced)
Enhanced benchmark data from the HuggingFace AI Dashboard — includes query metadata (query_set, intent), run metadata (run_name, run_date), and freshness flags for stale references.
This is the v2 enhanced dataset. The original dataset is at davidkling/hf-coding-tools-dashboard.
Dataset Structure
Split
Description
Rows
results
Enhanced results with query/run metadata and freshness flags
9146
queries… See the full description on the dataset page: https://huggingface.co/datasets/davidkling/hf-coding-tools-dashboard-v2.hf-coding-tools-dashboard-run-april12
HuggingFace AI Coding Tools Dashboard
Benchmark data from the HuggingFace AI Dashboard — tracking how AI coding tools (Claude Code, Codex, Copilot, Cursor) recommend HuggingFace products across 32 developer categories.
Dataset Structure
Split
Description
Rows
results
Full benchmark results with LLM responses, cost, tokens, latency, and product detection
8875
queries
Benchmark query definitions across 32 categories
263
runs
Run metadata and tool/model… See the full description on the dataset page: https://huggingface.co/datasets/davidkling/hf-coding-tools-dashboard-run-april12.