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initial updates for infer stuffs
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SWivid
117
README.md
117
README.md
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### Thanks to all the contributors !
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## News
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- **2024/10/08**: F5-TTS & E2 TTS base models on [🤗 Hugging Face](https://huggingface.co/SWivid/F5-TTS), [🤖 Model Scope](https://www.modelscope.cn/models/SWivid/F5-TTS_Emilia-ZH-EN).
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## Installation
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```bash
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docker build -t f5tts:v1 .
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```
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## Inference
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### 1. Basic usage
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```bash
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# cli inference
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f5-tts_infer-cli
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# gradio interface
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f5-tts_infer-gradio
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```
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### 2. More instructions
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- In order to have better generation results, take a moment to read [detailed guidance](src/f5_tts/infer/README.md).
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- The [Issues](https://github.com/SWivid/F5-TTS/issues?q=is%3Aissue) are very useful, please try to find the solution by properly searching the keywords of problem encountered. If no answer found, then feel free to open an issue.
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## [Training](src/f5_tts/train/README.md)
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## [Evaluation](src/f5_tts/eval/README.md)
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## Development
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Use pre-commit to ensure code quality (will run linters and formatters automatically)
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Note: Some model components have linting exceptions for E722 to accommodate tensor notation
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## Inference
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```python
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import gradio as gr
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from f5_tts.gradio_app import app
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with gr.Blocks() as main_app:
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gr.Markdown("# This is an example of using F5-TTS within a bigger Gradio app")
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# ... other Gradio components
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app.render()
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main_app.launch()
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```
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The pretrained model checkpoints can be reached at [🤗 Hugging Face](https://huggingface.co/SWivid/F5-TTS) and [🤖 Model Scope](https://www.modelscope.cn/models/SWivid/F5-TTS_Emilia-ZH-EN), or automatically downloaded with `inference-cli` and `gradio_app`.
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Currently support 30s for a single generation, which is the **TOTAL** length of prompt audio and the generated. Batch inference with chunks is supported by `inference-cli` and `gradio_app`.
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- To avoid possible inference failures, make sure you have seen through the following instructions.
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- A longer prompt audio allows shorter generated output. The part longer than 30s cannot be generated properly. Consider using a prompt audio <15s.
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- Uppercased letters will be uttered letter by letter, so use lowercased letters for normal words.
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- Add some spaces (blank: " ") or punctuations (e.g. "," ".") to explicitly introduce some pauses. If first few words skipped in code-switched generation (cuz different speed with different languages), this might help.
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### CLI Inference
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Either you can specify everything in `inference-cli.toml` or override with flags. Leave `--ref_text ""` will have ASR model transcribe the reference audio automatically (use extra GPU memory). If encounter network error, consider use local ckpt, just set `ckpt_file` in `inference-cli.py`
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for change model use `--ckpt_file` to specify the model you want to load,
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for change vocab.txt use `--vocab_file` to provide your vocab.txt file.
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```bash
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# switch to the main directory
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cd f5_tts
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python inference-cli.py \
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--model "F5-TTS" \
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--ref_audio "tests/ref_audio/test_en_1_ref_short.wav" \
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--ref_text "Some call me nature, others call me mother nature." \
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--gen_text "I don't really care what you call me. I've been a silent spectator, watching species evolve, empires rise and fall. But always remember, I am mighty and enduring. Respect me and I'll nurture you; ignore me and you shall face the consequences."
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python inference-cli.py \
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--model "E2-TTS" \
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--ref_audio "tests/ref_audio/test_zh_1_ref_short.wav" \
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--ref_text "对，这就是我，万人敬仰的太乙真人。" \
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--gen_text "突然，身边一阵笑声。我看着他们，意气风发地挺直了胸膛，甩了甩那稍显肉感的双臂，轻笑道，我身上的肉，是为了掩饰我爆棚的魅力，否则，岂不吓坏了你们呢？"
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# Multi voice
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# https://github.com/SWivid/F5-TTS/pull/146#issue-2595207852
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python inference-cli.py -c samples/story.toml
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```
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### Gradio App
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Currently supported features:
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- Chunk inference
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- Podcast Generation
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- Multiple Speech-Type Generation
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- Voice Chat powered by Qwen2.5-3B-Instruct
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You can launch a Gradio app (web interface) to launch a GUI for inference (will load ckpt from Huggingface, you may also use local file in `gradio_app.py`). Currently load ASR model, F5-TTS and E2 TTS all in once, thus use more GPU memory than `inference-cli`.
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```bash
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python f5_tts/gradio_app.py
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```
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You can specify the port/host:
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```bash
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python f5_tts/gradio_app.py --port 7860 --host 0.0.0.0
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```
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Or launch a share link:
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```bash
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python f5_tts/gradio_app.py --share
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```
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### Speech Editing
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To test speech editing capabilities, use the following command.
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```bash
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python f5_tts/speech_edit.py
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```
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## [Training](src/f5_tts/train/README.md)
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## [Evaluation](src/f5_tts/eval/README.md)
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## Acknowledgements
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