Text-to-Speech
ESPnet
PyTorch
English
audio
speech
instruction-following
singing-voice-synthesis
speech-language-model
Instructions to use espnet/bagpiper-tts-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ESPnet
How to use espnet/bagpiper-tts-sft with ESPnet:
from espnet2.bin.tts_inference import Text2Speech model = Text2Speech.from_pretrained("espnet/bagpiper-tts-sft") speech, *_ = model("text to generate speech from") - Notebooks
- Google Colab
- Kaggle
| { | |
| "artifact": "espnet/bagpiper-tts-sft", | |
| "format": "native ESPnet weight-only checkpoint", | |
| "weight_file": { | |
| "path": "model.pt", | |
| "bytes": 18188823609, | |
| "sha256": "168fe0aca32f4b1636e4ee2e63ef3880427be352bd6369a1f5ba3b49750f91da", | |
| "top_level_keys": ["module"], | |
| "tensor_count": 1382 | |
| }, | |
| "source": { | |
| "repo": "JinchuanTian/bagpipier_tts_ckpt", | |
| "repo_type": "dataset", | |
| "revision": "d70ecb45d579242d67da948d98a31ced3f854702", | |
| "path": "checkpoints/step_276698/global_step276686/mp_rank_00_model_states.pt", | |
| "bytes": 18188293711, | |
| "sha256": "d8a53f857760aab476896e486733f34c3ac9945dbbeedeea702c66eb75d457eb" | |
| }, | |
| "validation": { | |
| "source_tensors_equal": 1381, | |
| "added_tensor": "vocab_weight", | |
| "strict_load": "pass", | |
| "espnet_revision": "1992821bfb6d68c6636d1b75340b8b2b591bc015", | |
| "transformers": "5.5.4", | |
| "pytorch": "2.12.1+cu129", | |
| "gpu": "NVIDIA H100 80GB HBM3" | |
| } | |
| } | |