Instructions to use INCModel/Wan2.2-S2V-14B-MXFP8-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use INCModel/Wan2.2-S2V-14B-MXFP8-AutoRound with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("INCModel/Wan2.2-S2V-14B-MXFP8-AutoRound", 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: 395 Bytes
4ebe304 | 1 2 3 4 5 6 7 8 9 10 11 | {
"bits": 8,
"data_type": "mx_fp",
"group_size": 32,
"sym": true,
"enable_quanted_input": false,
"autoround_version": "0.13.0",
"block_name_to_quantize": "blocks,audio_injector.injector,audio_injector.injector_pre_norm_feat,audio_injector.injector_pre_norm_vec,audio_injector.injector_adain_layers",
"quant_method": "auto-round",
"packing_format": "auto_round:llm_compressor"
} |