{
 "schema_version": 1,
 "generated": "2026-10-31",
 "id": "swivid-f5-tts--run-f5-tts-in-docker-for-a-repeatable-setup",
 "repo": "SWivid/F5-TTS",
 "repo_url": "https://github.com/SWivid/F5-TTS",
 "repo_slug": "swivid-f5-tts",
 "title": "Run F5 TTS in a container instead of installing it",
 "page_title": "How to run F5 TTS in a container instead of installing it with F5 TTS",
 "summary": "Use the published image or build the Dockerfile so the CUDA and PyTorch setup is fixed.",
 "who": "A team that wants the same TTS setup on every machine.",
 "problem": "Matching CUDA, PyTorch and FFmpeg versions by hand breaks often.",
 "outcome": "A container that runs the CLI or the web interface the same way everywhere.",
 "steps": [
  "Build the image with `docker build -t f5tts:v1 .` from the repo, or pull the published one",
  "Run the container from the registry with the README command for `ghcr.io/swivid/f5-tts:main`, mounting the f5-tts volume onto the Hugging Face hub cache and publishing port 7860",
  "To go straight to the web interface append `f5-tts_infer-gradio --host 0.0.0.0` to that run command",
  "For an NVIDIA machine copy the docker compose example in the README"
 ],
 "agent_prompt": "Using SWivid/F5-TTS, get the docker image running with the hub cache volume and port 7860, then generate one sample to prove the setup works.",
 "agents": [
  "claude-code",
  "codex",
  "cursor",
  "gemini-cli"
 ],
 "difficulty": "Intermediate",
 "time": "1 hour",
 "basis": "readme",
 "caveat": "Model weights download into the mounted cache volume on first run.",
 "category": "Content",
 "tags": [
  "Content"
 ],
 "lang": "",
 "requirements": [
  "Python 3.10 or newer, for example a conda env created with `conda create -n f5-tts python=3.11`",
  "PyTorch and torchaudio matched to your device, plus FFmpeg",
  "A reference WAV clip of the voice you want, and its transcript if you do not want ASR to transcribe it",
  "A GPU for comfortable speed; the published benchmarks use a single L20"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [
  {
   "tag": "platform",
   "notice": "The documented run commands pass --gpus=all, so they expect an NVIDIA container runtime."
  }
 ],
 "best": false,
 "score": 0.8,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/swivid-f5-tts/run-f5-tts-in-docker-for-a-repeatable-setup/",
 "md": "https://dedupedai.com/use-cases/swivid-f5-tts/run-f5-tts-in-docker-for-a-repeatable-setup/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/swivid-f5-tts--run-f5-tts-in-docker-for-a-repeatable-setup.json",
 "api_version": "v1"
}