Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
Japanese
Size:
10M - 100M
License:
File size: 2,066 Bytes
d33305e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 | ---
language:
- ja
pretty_name: lambda-corpus
license: other
task_categories:
- text-generation
tags:
- japanese
- pretraining
- corpus
- parquet
size_categories:
- 10M<n<100M
configs:
- config_name: default
data_files:
- split: train
path: "data/train-*.parquet"
- split: validation
path: "data/validation.parquet"
- split: test
path: "data/test.parquet"
---
# lambda-corpus
lambda-corpus is a Japanese text corpus for language model pretraining. It combines openly available Japanese datasets into a consistent format and provides predefined train, validation, and test splits.
## Purpose
The dataset is intended for pretraining of Japanese language models. It contains web documents, Wikipedia-derived text, academic grant records, and synthetic question-answer text.
## Source Data
| Source | Rows | Tokens | License |
| --- | ---: | ---: | --- |
| [KeisukeMiyamoto/CleanedFineWeb2Edu-jp](https://huggingface.co/datasets/KeisukeMiyamoto/CleanedFineWeb2Edu-jp) | 11,772,204 | 7.61B | ODC-BY |
| [hpprc/jawiki-bullet-points](https://huggingface.co/datasets/hpprc/jawiki-bullet-points) | 3,523,358 | 1.55B | CC BY-SA 4.0 |
| [kanhatakeyama/CommonCrawl-RAG-QA-Calm3-22b-chat](https://huggingface.co/datasets/kanhatakeyama/CommonCrawl-RAG-QA-Calm3-22b-chat) | 2,525,793 | 1.04B | Other |
| [hpprc/llmjp-kaken](https://huggingface.co/datasets/hpprc/llmjp-kaken) | 1,079,030 | 1.03B | CC BY 4.0 |
## Dataset Size
| Split | Rows |
| --- | ---: |
| train | 18,522,556 |
| validation | 189,174 |
| test | 188,655 |
| total | 18,900,385 |
The dataset contains approximately 11.23B tokens measured with the gemma 4 tokenizer.
## Columns
| Column | Description |
| --- | --- |
| `id` | Identifier inherited from the source dataset |
| `text` | Normalized document text |
| `output_tokens` | Number of tokens in `text`, measured with the gemma 4 tokenizer |
| `source` | Name of the source dataset |
## Example
```python
from datasets import load_dataset
dataset = load_dataset("KeisukeMiyamoto/lambda-corpus")
print(dataset["train"][0])
```
|