datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
claude-protein-binder-design
Claude protein binder design — data release v1.0
1,440 de novo miniprotein binders (50 to 120 residues) against 16 targets, designed by two Claude models operating as autonomous protein-design agents (Mythos Preview, 900 designs; Opus 4.8, 540 designs) and characterized at two contract research organizations, Adaptyv Bio (cell-free expression; SPR/BLI kinetics with the design immobilized) and Twist Bioscience (Fc-fusion expression; capture SPR with a six-point antigen… See the full description on the dataset page: https://huggingface.co/datasets/Anthropic/claude-protein-binder-design.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.claude-opus-5-5-video-posts
Start here: actual code and training data
Last updated: 2026-09-29
Reproducibility guide: builder, converter, custom collator, validator, original tests, dependency pins and portable checks.
58 readable causal actions: full tool arguments, including actual write/edit code; no base64 images. 31 train / 27 eval actions from four captured episodes.
Agent-generated final code: actual scene.html and NOTES.md files, with verified write/edit replay. These are separate reconstructions… See the full description on the dataset page: https://huggingface.co/datasets/owenisas/claude-opus-5-5-video-posts.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.kimi-k2.6-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.
Kimi K2.6 Claude Code Traces
This directory contains raw agent trace files generated by teich.
All assistant responses were generated by moonshotai/kimi-k2.6.
JSONL files: 36
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/kimi-k2.6-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.cosmo-1B-claude_3h_feedbackclaude-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-opus-4.8-pi-tracesMore expensive than anticpated so you only get 4 lol :P
This 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.
Claude Opus 4.8 Pi Traces
This directory contains raw agent trace files generated by teich.
All assistant responses were generated by anthropic/claude-opus-4.8.
JSONL files: 4
Training-ready tools
A complete configured tools schema snapshot is… See the full description on the dataset page: https://huggingface.co/datasets/Quaxicron/claude-opus-4.8-pi-traces.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
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/abyss5912/claude.cosmo-1B-claude_promptclaude-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-opus-4.8-pi-tracesMore expensive than anticpated so you only get 4 lol :P
This 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.
Claude Opus 4.8 Pi Traces
This directory contains raw agent trace files generated by teich.
All assistant responses were generated by anthropic/claude-opus-4.8.
JSONL files: 4
Training-ready tools
A complete configured tools schema snapshot is… See the full description on the dataset page: https://huggingface.co/datasets/armand0e/claude-opus-4.8-pi-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/Sayyam6565/claude-fable-5-claude-code.funes-AlinCiocan-fable-5-claude-code-traces
Funes recall store — AlinCiocan Fable-5 Claude Code traces
A funes recall store built by indexing
AlinCiocan/fable-5-claude-code-traces
(18 Claude Code sessions run on Fable 5).
What this is
This is not a raw trace dataset — it is a pre-built funes index: the source
sessions chunked into content blocks and embedded, stored as a
Lance table (chunks.lance).
Source
AlinCiocan/fable-5-claude-code-traces (18 sessions)
Chunks
3,889
Embedding model… See the full description on the dataset page: https://huggingface.co/datasets/dacorvo/funes-AlinCiocan-fable-5-claude-code-traces.