Limbu Piper TTS (LIFWBT)

Work-in-progress Limbu TTS trained from timestamped cleaned Bible audio chunks.

Training shape

  • Base: Piper+ multilingual base warmstart
  • Data kept: 5,989 chunks / about 18.37 hours
  • Speaker layout: one real speaker slot (limbu_bible_voice) plus one unused compatibility slot
  • Audio: 22.05 kHz
  • Duration predictor: trainable
  • WavLM discriminator: disabled for this run

Files

  • best/best.ckpt: selected best checkpoint after training finalization
  • best/config.json: matching Piper dataset config
  • samples/warmstart-base/: fixed evaluation renders before Limbu fine-tuning
  • samples/<epoch>/: fixed evaluation renders from different epoch checkpoints
  • metadata/: eval manifest, preprocessing stats, speaker estimate, and progress summaries

Best checkpoint selection uses the lowest TensorBoard val_loss by epoch when available; otherwise it falls back to the latest epoch checkpoint.

Current best

  • Tag: epoch-0119-step-117360
  • Source checkpoint: epoch=119-step=117360.ckpt
  • Epoch: 119
  • Step: 117360

Uploaded epoch sample checkpoints

  • epoch-0229-step-224940
  • epoch-0234-step-229830
  • epoch-0239-step-234720
  • epoch-0244-step-239610
  • epoch-0249-step-244500
  • epoch-0029-step-29340
  • epoch-0039-step-39120
  • epoch-0049-step-48900
  • epoch-0054-step-53790
  • epoch-0059-step-58680
  • epoch-0064-step-63570
  • epoch-0069-step-68460
  • epoch-0074-step-73350
  • epoch-0079-step-78240
  • epoch-0084-step-83130
  • epoch-0089-step-88020
  • epoch-0009-step-9780
  • epoch-0094-step-92910
  • epoch-0099-step-97800
  • last-v1
Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support