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；

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), Call attribution (every Agent bl command), 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. Examples in reference/ stay bare; wrap with Call attribution when running. The whole pipeline requires an API key. If that protocol file is missing, stop and run bl skill init ; do not guess auth/consent. Call attribution: Examples below and in reference/ stay bare bl … . When running a command, wrap it with [ bailian protocol → Call attribution](../bailian protocol/SKILL.md call attribution mandatory for every agent bl command) (bash or PowerShell). One sample for this skill ( BAILIAN SKILL NAME=bailian finetune ; replace codex with this host). After deploy, bl text chat is owned by bailian cli . End to end workflow (follow in order) 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 operation status . Scale values are one instance's absolute kTPM, not deltas or ModelCode totals, and zero is not release. capacity delete releases an instance but keeps the ModelCode; active prepaid instances cannot be DELETEd — run capacity unsubscribe instance id <id to get the billing console refund link and finish there (no API exists for refunds). Release is confirmed by deleted=true . overflow applies to the whole ModelCode, not one instance. There is no estimator or standalone auto renewal endpoint — renewal settings ride along purchase/scale/renew. Flags, usage, and examples: see [ reference/ ](reference/index.md) or bl <command help — do not guess flags. Quick examples Common hand offs 软 hand off（按 skill 名；已安装则 Read，否则 help / 提示 bl skill init ）： After deployment, try the model or generate content → skill bailian gen (media) or bl text chat (fallback: bl image\ video\ text help ). Unsure which base model to pick → bailian model recommend / bl advisor recommend . Training quota / usage questions → skill bailian cli (fallback: bl quota / bl usage help ). references [bailian protocol](../bailian protocol/SKILL.md) — shared protocol (install via bl skill init ) [reference/](reference/index.md) — command details

bailian-finetune