---

name: hf-family-workflows description: "Operate Hugging Face remote-code and Gradio-style workflows for MOSS-TTS family models." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

hf-family-workflows

Use this sub-skill when the task is to run, adapt, or debug the Hugging Face AutoProcessor/AutoModel remote-code workflows or the Gradio-style UI parameters for the MOSS-TTS family.

Best-fit requests

• MOSS-TTS-v1.5 or MOSS-TTS 1.0 direct TTS, voice cloning, continuation, duration control, language tags, Pinyin, IPA, or [pause X.Ys] prompt control.
• MOSS-TTSD-v1.0 multi-speaker dialogue generation with [S1]...[S5] tags and per-speaker reference audio.
• MOSS-VoiceGenerator text + natural-language voice-instruction prompts.
• MOSS-SoundEffect v1 text-to-sound prompts through the Delay-family Hugging Face API.
• Choosing between Delay and Local architectures for non-streaming Hugging Face generation.
• Selecting attn_implementation, dtype/device, model ID, codec path, sampling parameters, or Gradio launch flags.
• Normalizing prompt text before sending it to build_user_message.
• Diagnosing import, package exposure, model download/cache, remote-code, reference-audio, or mixed checkpoint/code failures.

Route elsewhere

• Torch-free / low-memory llama.cpp, GGUF, ONNX, or TensorRT backend: ../llama-cpp-backend/SKILL.md.
• MOSS-TTS-Local-Transformer-v1.5 realtime streaming app or streaming decode internals: ../local-v15-streaming/SKILL.md.
• MOSS-TTS-Realtime voice-agent, FastAPI, SSE, or multi-turn streaming sessions: ../realtime-voice-agent/SKILL.md.
• Fine-tuning, data JSONL construction, audio_codes, training launchers, or post-finetune checks: ../finetuning-data-prep/SKILL.md.
• MOSS-SoundEffect-v2.0 DiT/Flow-Matching pipeline: ../soundeffect-v2/SKILL.md.

Operating map

1. Start with references/hf-generation-workflows.md for concrete generation recipes, model IDs, Gradio-style flags, and prompt patterns.
2. Use references/api-reference.md when you need exact build_user_message, conversation shape, processor modes, audio-code, and hyperparameter contracts.
3. Use references/model-packaging.md before changing model/code/codec packaging, using fused checkpoint layouts, or diagnosing package exposure.
4. Use references/troubleshooting.md for known failure signatures and fixes.
5. Use scripts/normalize_tts_text.py for safe stdlib-only prompt cleanup; it can run from any current working directory.

Quick safeguards

• Always pass trust_remote_code=True for Hugging Face AutoProcessor and AutoModel loads.
• Prefer CUDA + bfloat16 for 8B models. CPU can load only in very constrained smoke tests and is usually impractical for generation.
• Keep model code, config, n_vq, tokenizer, and audio codec matched. Mixed Delay/Local/TTSD/VoiceGenerator code and checkpoints often produce shape errors or gibberish.
• For v1.5 multilingual prompts, set the language field when known; for continuation, prepend the reference transcript to the text.
• Do not use this skill as proof that model download or full generation succeeded in the target runtime; those are runtime prerequisites to verify where the model will actually run.