Instructions to use developerabu/vits-tts-mnn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use developerabu/vits-tts-mnn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="developerabu/vits-tts-mnn", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("developerabu/vits-tts-mnn", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload vits_rasa_13_fp16.onnx
Browse files- vits_rasa_13_fp16.onnx +3 -0
vits_rasa_13_fp16.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c9e9c41d9674334e80e63082a7606d9e8945248f024a8fdd5295dbe9bc9cb826
|
| 3 |
+
size 63353809
|