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
| { | |
| "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" | |
| } |