| --- |
| license: other |
| license_name: mixed-upstream |
| license_link: https://huggingface.co/datasets/weilan55/k3f_regen_data#licensing |
| task_categories: |
| - text-generation |
| language: |
| - en |
| - zh |
| tags: |
| - speculative-decoding |
| - draft-model |
| - on-policy |
| - multi-turn |
| size_categories: |
| - 1M<n<10M |
| configs: |
| - config_name: v5_train |
| data_files: v5_train.jsonl |
| - config_name: v6_train |
| data_files: v6_train.jsonl |
| - config_name: longchat_allturn |
| data_files: longchat_allturn.jsonl |
| --- |
| |
| # K3-Flash regenerated corpora for draft-model training |
|
|
| On-policy responses generated by **`moonshotai/Kimi-K3-Flash`** over prompts taken |
| from public datasets, built for training speculative-decoding draft models |
| (EAGLE-3 / DSpark style). The prompts are upstream; **every assistant turn here is |
| K3-Flash's own output**, which is what makes the data on-policy for a draft that |
| has to predict this target. |
|
|
| No production or service traffic is included. Every row's `metadata.source` names |
| its upstream public dataset. |
|
|
| ## Files |
|
|
| | file | rows | what it is | |
| |---|---|---| |
| | `v5_train.jsonl` | 293,182 | depth-matched sample, deliberately skewed toward **bounded** asks (69.3% vs 45.4% in the internal baseline) | |
| | `v6_train.jsonl` | 1,013,914 | the full deduplicated pool, no ratio shaping | |
| | `longchat_allturn.jsonl` | 476,318 | **all-turn** regeneration of 47,651 long conversations: every intermediate assistant turn regenerated against the model's own earlier replies | |
|
|
| ### Schema |
|
|
| `v5_train` / `v6_train` — one conversation per row: |
|
|
| ```json |
| {"id": "...", "conversations": [{"role": "user", "content": "..."}, |
| {"role": "assistant", "content": "..."}], |
| "metadata": {"source": "WildChat-1M", "batch": "E", "n_assistant_turns": 4, |
| "depth_band": "4-7", "ask_shape": "bounded", |
| "supervised_kind": "text_only", "tail_is_assistant": true}} |
| ``` |
|
|
| `longchat_allturn` — one **generation** per row, pretokenized: |
|
|
| ```json |
| {"id": "lc_<conv>_gen2", "primary_id": "lc_<conv>", |
| "input_ids": [...], "loss_mask": [0,...,0,1,...,1], |
| "conversations": [...prefix..., {"role": "assistant", "content": "..."}], |
| "metadata": {"turn_index": 2, "n_turns": 9, "source": "WildChat-1M"}} |
| ``` |
|
|
| `loss_mask` is 1 exactly over the completion tokens, so `input_ids` is the true |
| on-policy sequence and the boundary is exact rather than re-derived. Rows of one |
| conversation share a `primary_id`; `turn_index` k was generated against a prefix |
| whose earlier assistant turns are the model's own outputs, not the source's. |
|
|
| ## Upstream prompt sources |
|
|
| | source | rows in v6 | upstream | |
| |---|---|---| |
| | OpenCodeInstruct | 365,160 | `nvidia/OpenCodeInstruct` | |
| | kimi-mtp-dataset | 172,412 | `lightseekorg/kimi-mtp-dataset` | |
| | WildChat-1M | 148,706 | `allenai/WildChat-1M` | |
| | aya_dataset | 111,545 | `CohereLabs/aya_dataset` | |
| | ultrachat_200k | 99,738 | `HuggingFaceH4/ultrachat_200k` | |
| | kimi-mtp-llava-mm | 97,094 | llava subset of kimi-mtp | |
| | glaive-function-calling-v2 | 19,259 | `glaiveai/glaive-function-calling-v2` | |
|
|
| ## Known limitations |
|
|
| **Multimodal rows carry no pixels.** The 97,094 `kimi-mtp-llava-mm` rows in |
| `v6_train` use image parts shaped `{"type":"image","url":...,"path":...}`. Common |
| loaders look for `item["image"]` or `item["image_url"]["url"]`, so with those this |
| resolves to no image and the row trains as text with a bare `<image>` placeholder. |
| Affected rows are flagged `metadata.mm_image_unreadable: true`. The original COCO |
| URLs are in the `url` field if you want to rehydrate them. |
|
|
| **`tail_is_assistant: false` rows** end on a non-assistant message, so a |
| last-turn-only supervision rule has no target on them. Flagged, not removed. |
|
|
| **Acceptance is dominated by the supervised turn's kind, not by topic.** Measured |
| on these corpora's family: turns that emit a tool call draft at tau ~4.0-4.3 while |
| plain-text turns sit at ~2.0-3.0. Within plain text, a *bounded* ask (translate, |
| list, extract, fix) drafts +0.4 to +0.65 above an open-ended one; conversation |
| depth is monotonically worse (1 turn ~2.74, 10+ turns ~2.02). CJK text, output |
| length, and markdown structure were each tested and did **not** explain the gap. |
| These corpora are ~99.9% plain-text-supervised, so they exercise the hard end. |
|
|
| **`v6_train` and `longchat_allturn` overlap** on 29,567 conversations (62% of |
| longchat) — both draw from WildChat/ultrachat. Deduplicate by first-user-turn if |
| you mix them. |
|
|
| **Held-out rows** matching an internal eval split were removed during the build; |
| this is not a general-purpose decontamination against public benchmarks. |
|
|
| ## Licensing |
|
|
| Each row's prompt inherits its upstream dataset's license (ODC-BY for WildChat, |
| MIT for ultrachat, and the respective terms for OpenCodeInstruct, aya, glaive and |
| kimi-mtp — check each before redistributing). The assistant turns are generated |
| output from `moonshotai/Kimi-K3-Flash` and are subject to that model's license. |
| Verify both chains apply to your use case. |
|
|
