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--- |
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datasets: |
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- facebook/multilingual_librispeech |
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language: |
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- it |
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base_model: |
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- SWivid/F5-TTS |
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pipeline_tag: text-to-speech |
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license: cc-by-4.0 |
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library_name: f5-tts |
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--- |
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This is an Italian finetune for F5-TTS |
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Italian only so can't speak english properly |
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Trained over 247+h hours of "train" split of facebook/multilingual_librispeech dataset, 6717 steps for Epoch: |
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- catastrophic failure (the model forgot english) |
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- italian pronunciation not perfect (there are lot of checkpoints to let you play with and extend training, maybe with different datasets) |
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# Current most trained model |
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italian_59kh/model_280800.safetensors (41.8 Epoch) |
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## folder structure: |
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``` |
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| - italian_59kh |
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| | - checkpoints |
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``` |
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### italian_59kh |
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Contains the weight at specific steps, the higher the number, the further it went into training. |
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Weights in this folder can't be used to resume training, use checkpoints instead. |
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### italian_59kh/checkpoints |
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Contains the weight of the checkpoints at specific steps, the higher the number, the further it went into training. |
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Weights in this folder can be used as starting point to continue training. |
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The run.py file is an example of how to extract the wav files and produce the metadata.csv to use for training |
