Instructions to use NbAiLab/salmon-f5-tts-north-sami with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NbAiLab/salmon-f5-tts-north-sami with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("NbAiLab/salmon-f5-tts-north-sami", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Add files using upload-large-folder tool
Browse files- setting.json +20 -0
setting.json
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{
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"exp_name": "F5TTS_Base",
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"learning_rate": 1e-05,
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"batch_size_per_gpu": 3200,
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"batch_size_type": "frame",
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"max_samples": 64,
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"grad_accumulation_steps": 1,
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"max_grad_norm": 1,
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"epochs": 500,
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"num_warmup_updates": 300,
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"save_per_updates": 1000,
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"last_per_steps": 1000,
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"finetune": false,
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"file_checkpoint_train": "",
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"tokenizer_type": "char",
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"tokenizer_file": "",
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"mixed_precision": "none",
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"logger": "wandb",
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"bnb_optimizer": false
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}
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