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
File size: 534 Bytes
7e9a1e0 334353a 7e9a1e0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | {
"_class_name": "Decoder",
"_diffusers_version": "0.37.0",
"attn_resolutions": [],
"attn_type": "vanilla",
"causality_axis": "height",
"ch": 128,
"ch_mult": [
1,
2,
4
],
"dropout": 0.0,
"give_pre_end": false,
"is_causal": true,
"mel_bins": 64,
"mel_hop_length": 160,
"mid_block_add_attention": false,
"norm_type": "pixel",
"num_res_blocks": 2,
"out_ch": 2,
"resamp_with_conv": true,
"resolution": 256,
"sample_rate": 16000,
"tanh_out": false,
"temb_ch": 0,
"z_channels": 8
}
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