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name: text-modeling description: "Route easy12306 text prompt classifier training, fine-tuning, asset inspection, and prediction tasks." disable-model-invocation: true metadata: disco-role: operating root-skill: easy12306 license: Artistic 2.0

text-modeling

Use this sub-skill when the user wants to inspect, train, fine-tune, diagnose, or use the easy12306 text prompt classifier: the CNN that maps cropped Chinese instruction-text images to the repository's 80-class label vocabulary.

Route here when

• The task mentions texts.npz, texts.v2.npz, data.npy, labels.npy, model.v1.0.h5, model.v1.9.h5, model.v2.0.h5, or deployed text model.h5 artifacts.
• The user asks how the cropped prompt-text model is trained, fine-tuned, normalized, reshaped, or validated.
• The user needs to inspect whether a text-training dataset, label file, or text model artifact is compatible before starting an expensive training run.
• The task is about converting text-crop predictions into 80-label probabilities or grouping text crops by predicted label index.

Route away

• Image-tile classifier training or 12306.image.model.h5 work belongs in ../image-modeling/SKILL.md.
• Captcha crop extraction, text-crop construction, hash grouping, dataset assembly, or OCR-assisted labeling belongs in ../data-preparation/SKILL.md.
• End-to-end captcha inference with pretrained artifacts belongs in ../inference/SKILL.md.

Load these references

1. references/workflows.md for safe inspection, base training, v1.9/v2.0 fine-tuning, deployed prediction, and _predict/show output workflows.
2. references/api-reference.md for distilled function behavior, array schemas, architecture details, and artifact names.
3. references/troubleshooting.md for Keras/TensorFlow compatibility, label-encoding failures, missing artifacts, and expensive-training guidance.
4. Use scripts/inspect_text_training_assets.py before training or loading user-supplied text assets.

Shared root references expected after integration: ../../references/label-vocabulary.md for the 80-label index order and ../../references/model-artifacts.md for model filename ownership.

Operating rules

• Prefer inspection and schema validation before training. The base training routine runs 100 epochs, fine-tuning can add another 100 epochs, and CPU runs may be slow.
• Use Python 3.11 with Keras/TensorFlow 2.15-compatible APIs for the legacy Keras surface. Keras 3 is risky for this repository family because legacy keras.preprocessing APIs used by sibling scripts are removed or moved.
• Do not rely on the original source checkout for runtime instructions. This sub-skill distills the relevant text-modeling contracts and bundles the safe asset-inspection helper.
• Do not mix this text model with the image-tile model: both use the same 80-label vocabulary but consume different inputs and save different model artifacts.