entry dict | stats dict |
|---|---|
{
"repo": "LLM-OS-Models/LFM2.5-KO-Dataset-Index-and-Sources",
"kind": "source_index",
"path": "/home/work/.data/lfm2_ko_sft/downloads/LLM-Ko-Datasets",
"description": "Snapshot of gyunggyung/LLM-Ko-Datasets README/LICENSE used as a dataset index while building the SFT mix."
} | {
"path": "/home/work/.data/lfm2_ko_sft/downloads/LLM-Ko-Datasets",
"size_bytes": 106659,
"file_count": 31
} |
LFM2.5-KO-Dataset-Index-and-Sources
Snapshot of gyunggyung/LLM-Ko-Datasets README/LICENSE used as a dataset index while building the SFT mix.
This dataset is part of the LFM2.5-8B-A1B-KO-SFT / Agentic SFT workflow.
- Main SFT model: https://huggingface.co/LLM-OS-Models/LFM2.5-8B-A1B-KO-SFT
- CPT base model: https://huggingface.co/LLM-OS-Models/LFM2.5-8B-A1B-KO-CPT-FULL
- Agentic follow-up model: https://huggingface.co/LLM-OS-Models/LFM2.5-8B-A1B-KO-Agentic-SFT
- SFT GitHub: https://github.com/gyunggyung/LFM25-KO-SFT
- CPT GitHub: https://github.com/gyunggyung/LFM25-KO-CPT
Source Attribution
- Snapshot of https://github.com/gyunggyung/LLM-Ko-Datasets README/LICENSE.
Additional public references:
- Liquid LFM base model: https://huggingface.co/LiquidAI/LFM2.5-8B-A1B
- Liquid chat template docs: https://docs.liquid.ai/lfm/key-concepts/chat-template
- Liquid tool-use docs: https://docs.liquid.ai/lfm/key-concepts/tool-use
- Legalize-KR organization: https://github.com/legalize-kr
- KoTSQA v2.0: https://huggingface.co/datasets/etri-lirs/KoTSQA-v.2.0
- Korean dataset index reviewed for candidates: https://github.com/gyunggyung/LLM-Ko-Datasets
Notes
- This is an index/reference artifact, not a training corpus by itself.
- It documents Korean dataset candidates reviewed while building the KO SFT mix.
Summary
| field | value |
|---|---|
| kind | source_index |
| sample count | n/a |
| token count | n/a |
| max sequence / sample length | n/a |
| uploaded size bytes | 106659 |
Format
raw_lfm_chat_jsonl: JSONL rows with atextfield containing LFM ChatML-like conversation text.prepared_tokenized: NumPy response-only SFT arrays built with the LFM tokenizer:tokens.npyepoch_0/inst_start.npyepoch_0/inst_len.npyepoch_0/resp_start.npyepoch_0/resp_len.npytokenizer.json
Local Source Path
/home/work/.data/lfm2_ko_sft/downloads/LLM-Ko-Datasets
License And Usage Notes
This release republishes preprocessing artifacts used for the LFM2.5 Korean CPT/SFT workflow. Source components come from multiple public or locally prepared datasets, so downstream users should verify each upstream source license before redistribution or commercial use. Legal and finance examples are for model training/evaluation only and are not legal, financial, or investment advice.
Stats
{
"path": "/home/work/.data/lfm2_ko_sft/downloads/LLM-Ko-Datasets",
"size_bytes": 106659,
"file_count": 31
}
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