Text-to-Speech
Transformers
Safetensors
Iloko
speecht5
text-to-audio
philippines
philippine-languages
# Load model directly
from transformers import AutoProcessor, AutoModelForTextToSpectrogram
processor = AutoProcessor.from_pretrained("sapinsapin/speecht5_tts-pld-ilo")
model = AutoModelForTextToSpectrogram.from_pretrained("sapinsapin/speecht5_tts-pld-ilo", device_map="auto")Quick Links
speecht5_tts-pld-ilo
microsoft/speecht5_tts finetuned on
sapinsapin/pld.
Trained for 1000 steps on 1761 clips (batch 4×8, lr 1e-05, fp32 + gradient checkpointing). Synthesized listen-test samples are in samples/ (speechbrain x-vector speaker conditioning + microsoft/speecht5_hifigan vocoder).
| metric | value |
|---|---|
| eval_loss | 0.3924 |
Trained with finetune_tts.py from the
halohalo pipeline; the dataset
adapter normalizes each corpus to (audio@16k, text, speaker_id) so corpora
are swappable with a --dataset flag.
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Model tree for sapinsapin/speecht5_tts-pld-ilo
Base model
microsoft/speecht5_tts
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="sapinsapin/speecht5_tts-pld-ilo")