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training-export-and-deployment

training-export-and-deployment

Routes PaddleOCR users to training, export, deployment, and config-maintenance workflows.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: training-export-and-deployment description: "Routes PaddleOCR users to training, export, deployment, and config-maintenance workflows." metadata: disco-role: operating disable-model-invocation: true license: Apache 2.0

Training, Export, and Deployment

Use this route when the task is about training, evaluating, exporting, or deploying PaddleOCR models, or when the user needs to inspect config-driven launch paths rather than run a simple inference command.

Handle these tasks here

  • Config-driven training and evaluation.
  • Exporting models and inspecting training/program YAML.
  • Deployment decisions across serving, ONNX, C++, mobile, and high-performance inference paths.
  • TIPC and other long-tail regression evidence.

Route away from here

  • Everyday local OCR inference belongs in local-ocr-pipelines.
  • Document parsing and Office conversion belong in document-parsing-and-conversion.
  • Hosted API or MCP work belongs in cloud-api-and-integrations.

Read these references

Use the bundled script

What future agents should know

  • The source tools/ scripts and deploy/ tree are evidence for the public workflow, but they are not the runtime skill's execution surface.
  • Training and export are long-running and backend-sensitive. Use the references to choose the command shape, then validate the config before starting a job.
  • Treat tests/test_program_safe_yaml.py and similar config-safety tests as evidence for parser behavior, not as a substitute for real training.
  • Keep deployment choices separate: a serving path, an ONNX path, a C++ path, and a mobile path are not interchangeable.

Common triggers

  • "How do I train PaddleOCR on my dataset?"
  • "What config keys does program.py understand?"
  • "How do I export a model or choose a deployment backend?"
  • "Why did my deployment or checkpoint step fail?"
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