Instructions to use Aarjan/swar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- F5-TTS
How to use Aarjan/swar 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
Commit History
Today
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Cloner: guard against empty transcripts overflowing F5's window
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Model card: playground is free to try
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Model card: link the Swar Playground
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Yesterday
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Model card: cloning benchmark numbers on v1.1 scoring
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app: turn on the English model when swar_v6_ema.pt is in the repo
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app: English sentences use swar_v6_ema.pt (wrong sounds 20.4% -> 8.6%); Nepali output unchanged
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app: cloner English fixes (syllable pacing, measured hard-word list, pick English takes by sounds)
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app: cloner English fixes (syllable pacing, measured hard-word list, pick English takes by sounds)
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app: cloner English fixes (syllable pacing, measured hard-word list, pick English takes by sounds)
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app: cloner English fixes (syllable pacing, measured hard-word list, pick English takes by sounds)
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Model card: name the benchmark for every number, add swar_v6_ema.pt
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Add swar_v6_ema.pt: second checkpoint, stronger on English and mixed Nepali-English (code-switch CER 5.24 vs 5.6); the main model stays podvoices_ema.pt
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6 days ago
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cloner app bundle
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model card
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cloner app bundle
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cloner app bundle
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cloner app bundle
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presets Maya and Aarav from model-made audio only
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final model (podvoices_ema, 2026-10-23)
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8 days ago
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Upload vocab.txt with huggingface_hub
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Kriti CTC ONNX
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initial commit
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