Instructions to use kumarx/indicf5-haryanvi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- F5-TTS
How to use kumarx/indicf5-haryanvi with F5-TTS:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Test safe checkpoint cadence
Browse files
tests/test_training_modes.py
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@@ -12,6 +12,8 @@ def test_training_modes_are_isolated_and_conservative():
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assert MODE_DEFAULTS["full"]["subset_size"] is None
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assert MODE_DEFAULTS["pilot"]["batch_size_per_gpu"] <= 1200
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assert MODE_DEFAULTS["full"]["grad_accumulation_steps"] >= 2
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def test_explicit_trainer_script_is_used(tmp_path: Path):
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assert MODE_DEFAULTS["full"]["subset_size"] is None
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assert MODE_DEFAULTS["pilot"]["batch_size_per_gpu"] <= 1200
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assert MODE_DEFAULTS["full"]["grad_accumulation_steps"] >= 2
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assert MODE_DEFAULTS["smoke"]["save_every"] >= 100000
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assert MODE_DEFAULTS["overfit"]["save_every"] >= 100000
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def test_explicit_trainer_script_is_used(tmp_path: Path):
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