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  1. README_REPO.md +3 -3
README_REPO.md CHANGED
@@ -72,7 +72,7 @@ An initial guidance on Finetuning [#57](https://github.com/SWivid/F5-TTS/discuss
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  Gradio UI finetuning with `finetune_gradio.py` see [#143](https://github.com/SWivid/F5-TTS/discussions/143).
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- ## Wandb Logging
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  By default, the training script does NOT use logging (assuming you didn't manually log in using `wandb login`).
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@@ -112,8 +112,8 @@ Currently support 30s for a single generation, which is the **TOTAL** length of
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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_path` 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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  python inference-cli.py \
 
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  Gradio UI finetuning with `finetune_gradio.py` see [#143](https://github.com/SWivid/F5-TTS/discussions/143).
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+ ### Wandb Logging
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  By default, the training script does NOT use logging (assuming you didn't manually log in using `wandb login`).
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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_path` 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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  python inference-cli.py \