sskj/datasets/README.md
shishi cd7b2d4a62 docs(datasets): add README with ShareGPT download instructions
The datasets/ directory is gitignored (large, re-downloadable), but later
agents need to know how to obtain the dataset when it is missing. Add a
tracked README that documents the download steps.

- datasets/README.md: documents the ShareGPT_V3_unfiltered_cleaned_split.json
  source (HF anon8231489123/ShareGPT_Vicuna_unfiltered), the hf-mirror.com
  download command for CN environments, the JSON validity check (94145
  entries), and the container path consistency note.
- .gitignore: change "datasets/" to "datasets/*" so the "!datasets/README.md"
  negation actually works (git cannot re-include a file under a fully-ignored
  directory). The dataset .json stays ignored; only README.md is tracked.
2026-07-28 17:02:19 +08:00

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# datasets/
本目录存放基准测试用的数据集文件。数据集本身**不入库**(体积大、可重新下载),
本说明文档是仓库中此目录唯一的跟踪文件。
如果运行实验时遇到 `FileNotFoundError` 指向本目录下的某个数据集,按下方说明下载。
---
## ShareGPT_V3_unfiltered_cleaned_split.json
`sglang.bench_serving --dataset-name random``random`(非 `random-ids`)模式下,
会用这个 ShareGPT 文件作为词表采样的种子语料。文件缺失时 bench_serving 会报错。
### 来源
HuggingFace 数据集 `anon8231489123/ShareGPT_Vicuna_unfiltered` 的清洗切分版:
```
https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json
```
文件约 **642 MB**94145 条多轮对话JSON 数组格式。
### 下载方法(国内环境用 hf-mirror 镜像)
HuggingFace 直连在国内通常不通,改用 `hf-mirror.com` 镜像:
```bash
# 在仓库根目录下执行
mkdir -p datasets
curl -L -o datasets/ShareGPT_V3_unfiltered_cleaned_split.json \
"https://hf-mirror.com/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json"
```
校验:
```bash
python3 -c "import json; d=json.load(open('datasets/ShareGPT_V3_unfiltered_cleaned_split.json')); print('OK, 条目数:', len(d))"
# 期望输出: OK, 条目数: 94145
```
### 下载方法(能直连 HuggingFace 时)
```bash
curl -L -o datasets/ShareGPT_V3_unfiltered_cleaned_split.json \
"https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json"
```
### 容器内路径一致性
实验脚本(`start_vllm_docker.sh`)已挂载 `/mnt:/mnt`,而本仓库位于
`/mnt/yy/sskj`,因此容器内数据集路径与宿主机一致,均为:
```
/mnt/yy/sskj/datasets/ShareGPT_V3_unfiltered_cleaned_split.json
```
`config.env` 里的 `DATASET_PATH="${ROOT_DIR}/datasets/ShareGPT_V3_unfiltered_cleaned_split.json"`
会正确解析到这个路径,无需额外配置。
### 注意
- 数据集文件被 `.gitignore` 忽略(`datasets/` 规则),本 README 通过 `!datasets/README.md`
例外规则入库。新增其它数据集说明文档时,同样需要在该例外规则中列出。
- 若实验只用 `--dataset-name random-ids`(基于生成的 token id无需种子语料
则不需要此文件;当前 910C 实验默认用 `random`,需要下载。