bailian-finetune
阿里云百炼模型精调训练入口：用户要精调、微调、训练自己的模型（fine-tune，支持 SFT / SFT-LoRA / DPO / DPO-LoRA / CPT， 覆盖文本、语音、图像）、校验或上传训练数据集、看训练进度和日志、挑 checkpoint、导出精调产物、 把专属模型部署成服务时使用 `bl dataset` / `bl finetune` / `bl deploy`。链路是 validate 校验数据 → upload 拿 file-id → finetune create 建任务 → watch 看进度 → export 导出 → deploy 上线，需要 API key； 写操作先用 `--dry-run` 预览。反触发：用户点名火山方舟/ark 的精调不走本 skill；只是要选哪个模型走 bailian-model-recommend；用现成模型生图生视频走 bailian-gen；百炼其他资源管理走 bailian-cli。 官方安装：`npx skills add modelstudioai/cli --all -g`（与共享协议 bailian-protocol 同装）。
Profile →npx skills add modelstudioai/cli --skill bailian-finetune --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Bailian fine-tuning pipeline (`bl dataset` / `bl finetune` / `bl deploy`) **CRITICAL — Before executing, MUST read the shared protocol in [`../bailian-protocol/SKILL.md`](../bailian-protocol/SKILL.md): Version & updates (pre-flight checklist), Setup & auth, and CLI errors: report an issue. Command details are authoritative in [`reference/`](reference/index.md) (dataset / finetune / deploy) and `bl <command> --help` — do not guess flags. The whole pipeline requires an API key. If that protocol file is missing, stop and run `npx skills add modelstudioai/cli --all -g`; do not guess auth/consent.** ## End-to-end workflow (follow in order) ``` 1. Validate data bl dataset validate --file train.jsonl [--schema chatml|dpo|cpt|tts|image] 2. Upload data bl dataset upload --file train.jsonl # returns a file-id 3. Create job bl finetune text|audio|image create --model <base> --datasets <file-id|path> 4. Watch progress bl finetune watch --job-id ft-xxx # or get / logs 5. Pick artifact bl finetune checkpoints --job-id ft-xxx 6. Export model bl finetune export --job-id ft-xxx --checkpoint ckpt-N --model-name my-model 7. Deploy service bl deploy text|audio|image create --model my-model --name my
- End-to-end workflow (follow in order)
- When to use which command
- Quick examples
- Common hand-offs
- references
bl dataset validate --file train.jsonl bl dataset upload --file train.jsonl bl finetune text create --model qwen3-8b --training-type sft-lora --datasets file-xxx bl finetune watch --job-id ft-xxx bl finetune export --job-id ft-xxx --checkpoint ckpt-3 --model-name my-qwen-sft bl deploy text create --model my-qwen-sft --name my-svc
What does the bailian-finetune skill do?
阿里云百炼模型精调训练入口：用户要精调、微调、训练自己的模型（fine-tune，支持 SFT / SFT-LoRA / DPO / DPO-LoRA / CPT， 覆盖文本、语音、图像）、校验或上传训练数据集、看训练进度和日志、挑 checkpoint、导出精调产物、 把专属模型部署成服务时使用 `bl dataset` / `bl finetune` / `bl deploy`。链路是 validate 校验数据 → upload 拿 file-id → finetune create 建任务 → watch 看进度 → export 导出 → deploy 上线，需要 API key； 写操作先用 `--dry-run` 预览。反触发：用户点名火山方舟/ark 的精调不走本 skill；只是要选哪个模型走 bailian-model-recommend；用现成模型生图生视频走 bailian-gen；百炼其他资源管理走 bailian-cli。 官方安装：`npx skills add modelstudioai/cli --all -g`（与共享协议 bailian-protocol 同装）。
How do I install it?
Run `npx skills add modelstudioai/cli --skill bailian-finetune --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From modelstudioai/cli, a repository with 289 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.