Instructions to use fal/LTX-2-FlashPack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/LTX-2-FlashPack with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fal/LTX-2-FlashPack", 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
| { | |
| "_class_name": "Decoder", | |
| "_diffusers_version": "0.37.0", | |
| "causal": false, | |
| "convolution_dimensions": 3, | |
| "decode_noise_scale": 0.025, | |
| "decode_timestep": 0.05, | |
| "decoder_blocks": [ | |
| [ | |
| "res_x", | |
| { | |
| "inject_noise": false, | |
| "num_layers": 5 | |
| } | |
| ], | |
| [ | |
| "compress_all", | |
| { | |
| "multiplier": 2, | |
| "residual": true | |
| } | |
| ], | |
| [ | |
| "res_x", | |
| { | |
| "inject_noise": false, | |
| "num_layers": 5 | |
| } | |
| ], | |
| [ | |
| "compress_all", | |
| { | |
| "multiplier": 2, | |
| "residual": true | |
| } | |
| ], | |
| [ | |
| "res_x", | |
| { | |
| "inject_noise": false, | |
| "num_layers": 5 | |
| } | |
| ], | |
| [ | |
| "compress_all", | |
| { | |
| "multiplier": 2, | |
| "residual": true | |
| } | |
| ], | |
| [ | |
| "res_x", | |
| { | |
| "inject_noise": false, | |
| "num_layers": 5 | |
| } | |
| ] | |
| ], | |
| "decoder_spatial_padding_mode": "reflect", | |
| "in_channels": 128, | |
| "norm_layer": "pixel_norm", | |
| "out_channels": 3, | |
| "patch_size": 4, | |
| "timestep_conditioning": false | |
| } | |