Instructions to use akshan-main/tiny-ltx-modular-pipe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use akshan-main/tiny-ltx-modular-pipe with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("akshan-main/tiny-ltx-modular-pipe", 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 blocks class to LTXAutoBlocks
Browse files- modular_model_index.json +1 -1
modular_model_index.json
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@@ -1,5 +1,5 @@
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{
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"_blocks_class_name": "
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"_class_name": "LTXModularPipeline",
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"_diffusers_version": "0.38.0.dev0",
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"scheduler": [
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{
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"_blocks_class_name": "LTXAutoBlocks",
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"_class_name": "LTXModularPipeline",
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"_diffusers_version": "0.38.0.dev0",
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"scheduler": [
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