Instructions to use susnato/tortoise-tts_dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use susnato/tortoise-tts_dev with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("susnato/tortoise-tts_dev", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Update model_index.json
Browse files- model_index.json +0 -4
model_index.json
CHANGED
|
@@ -1,9 +1,5 @@
|
|
| 1 |
{
|
| 2 |
"_class_name": "TortoiseTTSPipeline",
|
| 3 |
-
"scheduler": [
|
| 4 |
-
"diffusers.scheduler",
|
| 5 |
-
"KarrasDiffusionSchedulers"
|
| 6 |
-
],
|
| 7 |
"audio_candidate_model": [
|
| 8 |
"transformers",
|
| 9 |
"ClvpModelForConditionalGeneration"
|
|
|
|
| 1 |
{
|
| 2 |
"_class_name": "TortoiseTTSPipeline",
|
|
|
|
|
|
|
|
|
|
|
|
|
| 3 |
"audio_candidate_model": [
|
| 4 |
"transformers",
|
| 5 |
"ClvpModelForConditionalGeneration"
|