name: inference-and-model-zoo
description: "Use Coqui TTS Python APIs and model registry for released-model
inference, custom checkpoint loading, speaker/language selection, and safe
model download decisions."
disable-model-invocation: true
metadata:
disco-role: operating
license: MPL 2.0
Inference and Model Zoo
Use this sub-skill when a task asks for Python TTS.api.TTS inference, released model discovery, model registry queries, custom checkpoint loading for inference, speaker/language selection, or deciding whether it is safe to load/download a pretrained Coqui TTS model.
Start here
- For exact Python signatures and object responsibilities, read references/api-reference.md.
- For model-name grammar, registry counts, default vocoders, dynamic Fairseq/XTTS names, and license/TOS handling, read references/model-zoo.md.
- For copyable Python workflows, custom checkpoint patterns, XTTS/YourTTS voice cloning, and high-level streaming notes, read references/workflows.md.
- For predictable failures and recovery actions, read references/troubleshooting.md.
Safe helper scripts
- Run scripts/inspect_tts_models.py to count, filter, or query the installed registry. It is read-only and does not download model weights.
- Run scripts/synthesize_text.py only after choosing a model. It supports
--dry-run; when using a released --model-name, it refuses to load until --allow-download acknowledges possible downloads, cache writes, and TOS prompts.
Route boundaries
Operating cautions
- Coqui TTS 0.22.0 supports Python
>=3.9,<3.12; do not treat Python 3.12+ or 3.13+ import behavior as supported.
- Model listing and metadata queries are safe. Loading a released model can download large files, update the model cache, check hashes, and prompt for license/TOS acceptance.
- CUDA is optional for this skill. Use CPU for metadata and tiny validations; request/confirm GPU only for practical synthesis speed, XTTS/Bark/Tortoise workloads, or user-requested performance checks.