README.md

metadata

title: GEPARD
emoji: 🐆
colorFrom: yellow
colorTo: red
sdk: gradio
sdk_version: 5.49.1
python_version: '3.12'
app_file: app.py
pinned: false
license: apache-2.0
short_description: Spotted text-to-speech with voice cloning and text-CFG

🐆 GEPARD TTS

Inference Space for the Gepard autoregressive speech model (nineninesix/gepard-1.0 — a Qwen3.5 backbone with 32 FSQ audio heads, a Q-Former voice-cloning compressor, and DPO post-training).

Features

• Preset speakers — bundled voices stored as pre-encoded codec tokens (speakers/*.pt), no codec pass needed at request time.
• Voice cloning — record with the microphone or upload a clip; the reference is encoded with the NeMo nano codec and compressed into 8 speaker prefix tokens.
• Text classifier-free guidance — cfg_scale/cfg_frames sharpen text and voice adherence (defaults: temperature=0.3, cfg_scale=3).
• All generation knobs are exposed under Generation settings.

Configuration

config.yaml selects the checkpoint, codec, preset speakers and default generation parameters — re-point the Space without touching code.

Notes

• The model repo is private: set the HF_TOKEN Space secret.
• ZeroGPU: the model is loaded once at startup; each request only runs generation inside the GPU context.
• create_env.py re-pins transformers==5.3.0 at startup (NeMo downgrades it at build time) — it must run before any ML import in app.py.