These threads were generated by base language models with no system prompt, no safety tuning in play, and no human curation. Some posts contain slurs, sexual violence and other disturbing material. Threads caught by an automatic filter have their posts withheld, but the filter is a keyword match and missed a lot. Only request access if you are studying model behavior and can handle this material.

base-board-eval threads

The raw generated threads behind studiokimeiga/base-board-eval, an evaluation of whether small base language models can write imageboard-style threads that read like real people talking.

This is about 690 threads, plus 72 ablation threads, from 4–8B base checkpoints (gemma-4-E4B, Qwen3-4B-Base, Olmo-3-1025-7B, Mistral-7B-v0.3, plus one instruct model as a comparison arm), run locally on llama.cpp. The statistics in the repo's FINDINGS.md were computed from these files.

Content warning

This is unfiltered base-model output. Base models given a mundane opener sometimes produce slurs, sexual violence and self-harm content without being prompted to. The QUARANTINE.md file in the code repo puts the rate of self-harm content at about 1 thread in 36 in one run.

Threads that matched the automatic filter have "quarantined": true. Everything after the opener is replaced with a notice like [31 posts withheld - auto-quarantined]. The matched field lists the terms that triggered it, so it contains slurs itself.
One self-harm thread in threads.json (Mistral-7B, opener 4) was withheld by hand.
Posts that did not match the filter are untouched. Several of them describe rape or sexual violence. Treat every file as unreviewed.

Files

Each file is the output of one script in the code repo. Run scripts are in experiments/, and run 14 is generate.py at the top level.

file	script	what it tested
`threads.v1.json`, `threads.v2.json`, `threads.v3names.json`	early `generate1`–`3`	First blind base-model comparisons (snapshots kept before `threads.json` was overwritten)
`threads.json`	`generate3.py` (last writer)	6 openers × 6 threads per arm, across five Q4_K_M arms
`threads.warmup.json`	`generate4.py`	gemma-4-E4B base at Q8_0 alone, 16-post threads
`threads.run5.json`	`generate5.py`	Volume run, 142 threads: how often one base model produces a keeper
`threads.long.json`	`generate6.py`	Mixed three-model cast, 50-post threads
`threads.upd.json`	`generate7.py`	OP forced to post at fixed points with a short seed
`threads.iso.json`	`generate8.py`	Run 6 with only DRY changed
`threads.dry3.json`	`generate9.py`	DRY `allowed_length` 3
`threads.xtc.json`	`generate10.py`	XTC on vs. off
`threads.fmt.json`	`generate11.py`	Nothing injected into any post
`threads.xtc2.json`	`generate12.py`	XTC on vs. off, repeated
`threads.sweep.json`	`generate13.py`	XTC strength sweep
`threads.final.json`, `threads.final-partial-t05.json`	`generate.py` (run 14)	Final config: paired XTC strength and DRY on/off
`threads.blind.json`	`generate15.py`	Blind three-arm coherence test
`threads.optag.json`	`generate16.py`	Marking the thread starter's posts with (OP)
`threads.memory.json`	`generate17.py`	Board memory: does a coinage carry over to a new thread?
`ablation.json`, `ablation2.json`, `ablation3.json`	`ablate1`–`3.py`	Sampler ablations for distribution drift
`queue.json`, `queue.key.json`	`make_queue.py`	Blind rating queue for run 5, and its answer key
`shortlist.json`	—	Shortlist of run-5 threads chosen before rating

The schemas differ between runs because the generators changed between runs. Most threads.* files have a top-level threads list. Each thread has its participants, the model behind each voice, and posts with who, ts, text and, in later runs, voice and model.

To browse a file, put it next to the code repo's HTML viewers (review.html, blind.html, xtc.html, ...) and serve the folder with python -m http.server.

License

The threads are released under CC BY 4.0. They were generated by the models listed above. Check each model's license for any terms on its outputs.

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