datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/armand0e/claude-fable-5-claude-code.mimo-claude-code-traces-1k
MIMO Claude Code Traces
MIMO Claude Code Traces is a collection of coding-agent trajectories in a Claude Code-style environment. Each record contains a user coding task, the full multi-turn message trace, available tool schemas, assistant reasoning fields, tool calls, tool outputs, and metadata such as model name, category, duration, cost, token usage, and whether the trace used tools.
The traces were generated with mimo-v2.5-pro, MiMo's most capable model at the time of… See the full description on the dataset page: https://huggingface.co/datasets/choucsan/mimo-claude-code-traces-1k.fable-5-claude-code-traces
Fable 5 Claude Code Traces
A full, scrubbed release of Fable 5 Claude Code session traces for researchers studying real coding-agent behavior: multi-turn prompts, assistant responses, tool calls, command output, retries, and session-level workflow metadata.
This release keeps the full package intact: 18 sessions, 9,497 JSONL events, 0 excluded rows, and 0 quarantine files. The traces are preserved in the native agent-event format so they can be inspected in Hugging Face Agent… See the full description on the dataset page: https://huggingface.co/datasets/AlinCiocan/fable-5-claude-code-traces.minimax-m3-claude-code-tracesThis dataset was generated using teich by TeichAI
Prepare these datasets for supervised fine-tuning in just a few lines of code — see the Conversion section below.
Minimax M3 Claude Code Traces
This directory contains raw agent trace files generated by teich.
All assistant responses were generated by minimax/minimax-m3.
JSONL files: 31
Format
Each file is newline-delimited JSON representing a single captured agent session.
The trace schema is designed for… See the full description on the dataset page: https://huggingface.co/datasets/armand0e/minimax-m3-claude-code-traces.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/ArkhAngelLifeJiggy/claude-fable-5-claude-code.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/Thugshake54323/claude-fable-5-claude-code.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/Nemesispro/claude-fable-5-claude-code.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/Pq234/claude-fable-5-claude-code.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/ansulev/claude-fable-5-claude-code.claude-fable-5-claude-code-etheroi
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/developerjeremylive/claude-fable-5-claude-code-etheroi.claude-code-traces
Claude Code session traces for ultralazr/claude-code-traces
This dataset contains redacted Claude Code session traces exported with cc-share-hf. The traces were filtered to keep only sessions that passed deterministic redaction and LLM review.
Data description
Each file in data/ is a redacted Claude Code session in its native JSONL format (one entry per line). HuggingFace auto-converts these to Parquet with one row per session file and four columns:
Column… See the full description on the dataset page: https://huggingface.co/datasets/ultralazr/claude-code-traces.claude-fable-5-claude-code
claude-fable-5 Agent Traces
For training on this dataset I recommend using the teich package to convert to openai style chats. It parses and filters out things like hitting limits and model switches, etc. As well as knows the exact tool-schemas and descriptions for the tools used.
I encourage everyone to please upload their fable-5 traces from whatever harness they may have used. This is all valuable data and we need to pool it together to make something meaningful :)
To easily… See the full description on the dataset page: https://huggingface.co/datasets/AyoubChLin/claude-fable-5-claude-code.claude-code-traces-pt-brThis dataset was generated using teich by TeichAI
claude Agent Traces
This directory contains raw agent trace files generated by teich.
JSONL files: 20
Training-ready tools
Generated agent traces carry configured or recovered tool schemas so tools remain available for training even when a session did not call them.
Native Claude Code imports recover schemas for Claude Code and Claude Desktop built-ins, plus conservative name-derived MCP schemas, when the raw… See the full description on the dataset page: https://huggingface.co/datasets/DedeProGames/claude-code-traces-pt-br.qwen9b-coop-claude-code
qwen9b-coop-claude-code
Two-agent cooperative coding trajectories generated by running
CooperBench in coop mode on
the CooperData task set, using
Qwen/Qwen3.5-9B as the model and Claude Code (claude_code) as the
agent framework. Each pair runs two agents in parallel — one per feature —
coordinating via Redis messaging and a shared git remote.
The matched solo (single-agent) baseline is at
CooperBench/qwen9b-solo-claude-code.
Same task corpus, same model, same agent — only the… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen9b-coop-claude-code.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/ShaunGves/claude-fable-5-claude-code.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/rumeshprasanga6/claude-fable-5-claude-code.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/ronaldcmz/claude-fable-5-claude-code.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/paperworkmg/claude-fable-5-claude-code.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/yrrhall/claude-fable-5-claude-code.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/owenqwenllmwine/claude-fable-5-claude-code.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/Sayyam6565/claude-fable-5-claude-code.qwen3.7-plus-claude-codeThis dataset was generated using teich by TeichAI
Prepare these datasets for supervised fine-tuning in just a few lines of code — see the Conversion section below.
Qwen3.6 Plus Claude Code Traces
This directory contains raw agent trace files generated by teich.
All assistant responses were generated by qwen/qwen3.7-plus.
JSONL files: 7
Format
Each file is newline-delimited JSON representing a single captured agent session.
The trace schema is designed for… See the full description on the dataset page: https://huggingface.co/datasets/armand0e/qwen3.7-plus-claude-code.qwen9b-solo-claude-code
qwen9b-solo-claude-code
Single-agent coding trajectories generated by running
CooperBench in solo mode on
the CooperData task set, using
Qwen/Qwen3.5-9B as the model and Claude Code (claude_code) as the
agent framework. One agent implements both features in each task.
The matched coop (two-agent) version is at
CooperBench/qwen9b-coop-claude-code.
Same task corpus, same model, same agent — only the coordination differs, so
together they isolate the cooperation deficit.
At a… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen9b-solo-claude-code.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/Rights4AI/claude-fable-5-claude-code.claude-fable-5-code
Claude Fable 5 Coding and Math Dataset (Non-Thinking)
This repository contains a dataset of 603 coding and math-related prompts and responses from Claude Fable 5.
The generation of this dataset cost approximately $75.
Please note that this dataset is non-thinking. Fable 5 only supported adaptive thinking, and it decided not to think for these prompts, meaning there is no chain-of-thought/reasoning content in this dataset.
Origin of Prompts
The prompts in this… See the full description on the dataset page: https://huggingface.co/datasets/PawanKrd/claude-fable-5-code.claude-code-rev-benchmark
Benchmark Suite / 基准测试套件
Professional benchmark harness for this restored Claude Code repository.
面向本还原版 Claude Code 仓库的专业级 Benchmark 框架。
Original upstream repository / 原版仓库地址：https://github.com/anthropics/claude-code
Restored source repository / 还原版源码仓库地址：https://github.com/oboard/claude-code-rev
Commands / 命令
bun run bench:smoke - quick hybrid pass for local validation快速混合模式验证（本地冒烟）
bun run bench:full - full hybrid suite完整混合模式基准
bun run bench:offline -… See the full description on the dataset page: https://huggingface.co/datasets/roseking/claude-code-rev-benchmark.llama3.2-java-codegen-90sft-10meta-claude-v1
LLaMA 3.2 Java Code Generation Dataset (90% SFT, 10% Meta Annotated with Claude)
This dataset contains 100,000 examples for Java method generation based on natural language instructions. It is built from the CodeXGLUE text-to-code dataset and designed to support both pure supervised fine-tuning (SFT) and reflection-based meta-learning approaches using Claude 4 Sonnet as the critique model.
🚀 Trained Models
Two models have been trained on this dataset:
SFT Model:… See the full description on the dataset page: https://huggingface.co/datasets/Naholav/llama3.2-java-codegen-90sft-10meta-claude-v1.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/eishaanand/claude-fable-5-claude-code.claude-fable-5-claude-code
claude-fable-5 Agent Traces
It's worth noting that our team was working with Glint-Research to collect as much fable data as possible.
These are just the anonymized raw traces of both of our teams combined. This means that Glint-Research/Fable-5-traces was created from formatting and splitting up this same dataset. If you use one for your tune, don't use the other (it's the same exact data).
For training on this dataset I recommend using the teich package to convert to openai… See the full description on the dataset page: https://huggingface.co/datasets/bh890/claude-fable-5-claude-code.ClaudeCode-Anthropic
ClaudeCode in Anthropic Tools API format
About AgentIR Collection
This dataset is part of the AgentIR Collection.
AgentIR is an open-source compiler infrastructure for agentic trajectories (like LLVM/MLIR, but for agent traces).
Using AgentIR, you can convert any source trajectory format into multiple target formats.
Project: https://github.com/ravenSanstete/agentir
DSL: Define custom formats with *.agentir.yaml files
CLI: agentir dsl convert for one-command… See the full description on the dataset page: https://huggingface.co/datasets/WhitzardAgent/ClaudeCode-Anthropic.