/bailian-finetune

name: bailian-finetune
metadata:
  version: "2.3.0"
  requires:
    bins: ["bl"]
description: >-
  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 → 可选 compress 量化压缩 → 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：`bl skill init`（与共享协议 bailian-protocol 同装）。

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 `bl skill init`; 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 --base-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. Compress model  bl finetune compress templates --model my-model       # optional; full-parameter models only
                   bl finetune compress create --model my-model --template-id <template-id>
                   bl finetune compress watch --job-id quant-xxx --follow
8. Deploy service  bl deploy text|audio|image create --model-name <my-model|quantized-output> --display-name my-svc

• Unsure which training methods a base model supports → `bl finetune capability --base-model <base>` or `--training-type sft|sft-lora|dpo|cpt`.
• Text `--training-type` values: `sft` / `sft-lora` / `dpo` / `dpo-lora` / `cpt`. Audio bases include `cosyvoice-v3-flash`; image bases include `wan2.7-image-pro`.
• Deployment plans: audio defaults to `--plan mu`; text/image default to `lora`.
• For `risk: high` or `requires_confirmation`, follow `bailian-protocol`; never add `--yes` automatically.

When to use which command

| Intent | Command | | -------------------------------------- | ------------------------------------------------------------------------------------------------ | | Validate / upload training data | `bl dataset validate` / `upload` (`.jsonl` or `.zip`) | | Dataset list / detail / delete | `bl dataset list` / `get` / `delete` | | Create a fine-tuning job | `bl finetune text\|audio\|image create` | | Job list / detail / follow | `bl finetune list` / `get` / `watch` / `logs` | | Artifacts and export | `bl finetune checkpoints` / `export` | | Quantize / compress a full model | `bl finetune compress templates` / `create` / `watch` / `get` / `logs` / `list` | | Cancel / delete a compression job | `bl finetune compress cancel` / `delete` | | Cancel / delete a fine-tuning job | `bl finetune cancel` / `delete` | | Trainable capability lookup | `bl finetune capability` | | Deploy / lifecycle | `bl deploy text\|audio\|image create`, `list` / `get` / `update` / `scale` / `delete` / `models` | | Query throughput reservations | `bl deploy list --plan ptu` / `bl deploy get` | | Query capacity instances | `bl deploy capacity list` / `get` | | Query / wait for a capacity operation | `bl deploy operation get` / `wait` | | Buy / scale / renew / release capacity | `bl deploy capacity create` / `scale` / `renew` / `delete` | | Unsubscribe a prepaid instance | `bl deploy capacity unsubscribe` (builds the billing console refund link) | | Configure ModelCode overflow strategy | `bl deploy overflow` |

The `capacity list` / `get`, `operation get` / `wait` and `deploy list` / `get` queries are read-only. Capacity values are kTPM; effective, configured and target capacities are distinct. `deploy list --status` filters only the fetched page locally, with the server total left unfiltered. `operation get` reports status as data; `operation wait` exits non-zero on failure or timeout and refreshes capacity after success. Use IDs returned by the API; waiting never retries a write.

The `capacity create` / `scale` / `renew` / `delete` and `overflow` commands are high-risk writes: preview with `--dry-run`, then confirm with the runtime-injected `--yes`. Each write is submitted once and never auto-retried; HTTP 200 is not success, so pass `--wait` or check