Instructions to use fal/Wan2.1-VACE-14B-FlashPack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/Wan2.1-VACE-14B-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/Wan2.1-VACE-14B-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
Download text_encoder/config.json from fal/Wan2.1-VACE-14B-FlashPack: direct link, hf CLI and curl.
- Browser
- Download file 249 Bytes
-
https://huggingface.co/fal/Wan2.1-VACE-14B-FlashPack/resolve/main/text_encoder/config.json
- Command line
-
hf download hf://fal/Wan2.1-VACE-14B-FlashPack/text_encoder/config.json
-
curl -L -o config.json https://huggingface.co/fal/Wan2.1-VACE-14B-FlashPack/resolve/main/text_encoder/config.json
249 Bytes
| { | |
| "_class_name": "T5Encoder", | |
| "_diffusers_version": "0.35.1", | |
| "dim": 4096, | |
| "dim_attn": 4096, | |
| "dim_ffn": 10240, | |
| "init_weights": false, | |
| "num_buckets": 32, | |
| "num_heads": 64, | |
| "num_layers": 24, | |
| "shared_pos": false, | |
| "vocab": 256384 | |
| } | |