Instructions to use hf-internal-testing/tiny-LTX2Pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-LTX2Pipeline with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-LTX2Pipeline", 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
Upload LTX2Pipeline
Browse files- model_index.json +2 -2
model_index.json
CHANGED
|
@@ -6,7 +6,7 @@
|
|
| 6 |
"AutoencoderKLLTX2Audio"
|
| 7 |
],
|
| 8 |
"connectors": [
|
| 9 |
-
"
|
| 10 |
"LTX2TextConnectors"
|
| 11 |
],
|
| 12 |
"processor": [
|
|
@@ -34,7 +34,7 @@
|
|
| 34 |
"AutoencoderKLLTX2Video"
|
| 35 |
],
|
| 36 |
"vocoder": [
|
| 37 |
-
"
|
| 38 |
"LTX2Vocoder"
|
| 39 |
]
|
| 40 |
}
|
|
|
|
| 6 |
"AutoencoderKLLTX2Audio"
|
| 7 |
],
|
| 8 |
"connectors": [
|
| 9 |
+
"diffusers",
|
| 10 |
"LTX2TextConnectors"
|
| 11 |
],
|
| 12 |
"processor": [
|
|
|
|
| 34 |
"AutoencoderKLLTX2Video"
|
| 35 |
],
|
| 36 |
"vocoder": [
|
| 37 |
+
"diffusers",
|
| 38 |
"LTX2Vocoder"
|
| 39 |
]
|
| 40 |
}
|