cetusian/GeneralThought-Qwen3-filtered

GeneralThought — Qwen3-filtered reasoning SFT

A drop-in SFT mix of general-reasoning chain-of-thought traces, pre-sanitized for Qwen3 models. Same records as the upstream filter, re-shaped into the messages schema expected by trl.SFTTrainer / transformers.apply_chat_template, with one critical fix that prevents a silent NaN failure on Qwen3 training with control-token-aware recipes (e.g. FP8 / NVFP4 hybrid attention).

What's in it

27,776 records, one line of JSONL each:

{
  "messages": [
    {"role": "system", "content": "You are a careful reasoner..."},
    {"role": "user",   "content": "<question>"},
    {"role": "assistant",
     "content": "<think>\n<reasoning>\n</think>\n\n<answer>"}
  ]
}

All rendered chat-template lengths ≤ 4,096 tokens under the Qwen3 tokenizer. Distribution: p50 = 1,108, p95 = 2,619, max 4,094. Every assistant turn contains exactly one <think> / </think> pair (records with duplicated control-tokens mid-reasoning were dropped).

Pure reasoning only. Zero records contain tool-calling artifacts (<tool_call>, <tools>, or OpenAI tool_calls blocks). If you want to teach tool use, do it in a later stage (e.g. RL); this dataset is for the CoT prior.

Why "Qwen3-filtered"

Qwen3's tokenizer treats the following as dedicated single control-token IDs rather than multi-token text:

Substring	Qwen3 token ID
<think> / </think>	151667 / 151668
<tool_call> / </tool_call>	151657 / 151658
<tool_response> / </tool_response>	151665 / 151666

If any of those strings appear verbatim inside a system or user message (for instance, in an instruction like "Reason inside <think>...</think> tags"), the tokenizer emits real control tokens outside the assistant's completion span. Certain attention/normalisation paths in FP8 and NVFP4 hybrid training recipes assume those IDs only appear in assistant spans, and silently produce NaN loss from step 0.

This dataset's system prompt describes the reasoning wrapper in neutral English — only the assistant's completion contains <think>...</think> — so the data is safe across recipes. Records longer than 4,096 tokens are also dropped, since mid-<think> truncation leaves unpaired control tokens with the same symptom.

Works out of the box with:

• transformers + trl.SFTTrainer (apply_chat_template)
• Surogate's type: conversation, messages_field: messages
• Any framework that tokenizes via the Qwen3 chat template

Smoke-verified on Qwen3-8B + LoRA (r=32): clean finite loss from step 0 with both bf16 and fp8-hybrid recipes.

Quick start

from datasets import load_dataset
from transformers import AutoTokenizer

ds  = load_dataset("cetusian/GeneralThought-Qwen3-filtered", split="train")
tok = AutoTokenizer.from_pretrained("Qwen/Qwen3-8B")

rendered = tok.apply_chat_template(ds[0]["messages"], tokenize=False)
print(rendered[:400])

License and attribution

This mix: Apache-2.0.

It is a derivative of natolambert/GeneralThought-430K-filtered (Apache-2.0), which is itself a commercial-safe subset of GeneralReasoning/GeneralThought-430K (MIT, per-question licenses vary; commercial-incompatible rows were already removed in the natolambert filter).

Please credit the upstream sources:

@misc{generalthought_430k,
  title  = {GeneralThought-430K},
  author = {GeneralReasoning},
  year   = {2025},
  url    = {https://huggingface.co/datasets/GeneralReasoning/GeneralThought-430K}
}

@misc{generalthought_filtered,
  title  = {GeneralThought-430K-filtered},
  author = {Nathan Lambert},
  year   = {2025},
  url    = {https://huggingface.co/datasets/natolambert/GeneralThought-430K-filtered}
}

Changes vs. the upstream filter

• Re-shaped into the messages list-of-dict format (system / user / assistant) used by trl.SFTTrainer.
• Stripped prepended instruction boilerplate from the user question.
• Rewrote any literal <think>…</think> references in the system prompt as neutral English — only the assistant's completion carries the actual <think>…</think> control tokens.
• Dropped records whose rendered chat-template length exceeds 4,096 Qwen3 tokens.
• Removed any tool-calling / <tools> records — this release is reasoning-only.
• Dropped records where an assistant turn contained more than one <think> or </think> substring (stray control-token emissions mid-reasoning).
• Dropped records whose message content contained any literal Qwen3 control-token substring (<|im_start|>, <|im_end|>, <|endoftext|>, <tool_call>, <tool_response>, <tools> and their closers). The tokenizer emits these as dedicated single-ID control tokens inside the text itself — same NaN / mask- confusion hazard class as mid-<think> truncation.

No questions, reasoning traces, or answers were altered beyond that.