Instructions to use wfen/Cosmos3-Nano-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wfen/Cosmos3-Nano-FP8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wfen/Cosmos3-Nano-FP8", 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
| { | |
| "recipe": "fp8", | |
| "weight_only": true, | |
| "quant_lmhead": true, | |
| "modelopt_artifact": "transformer/modelopt_quantized.pt", | |
| "loader": "Cosmos3OmniTransformer.from_config + modelopt.restore_from_modelopt_state + safetensors load_state_dict", | |
| "exclusions": [ | |
| "embed_tokens", | |
| "*norm*", | |
| "time_embedder", | |
| "proj_in", | |
| "proj_out", | |
| "audio_*", | |
| "action_*" | |
| ], | |
| "scale_layout": { | |
| "weight_scale_suffixes": [ | |
| "_amax", | |
| "_scale" | |
| ], | |
| "global_scale_suffixes": [], | |
| "n_weight": 802, | |
| "n_scale": 1010, | |
| "granularity": "per-tensor" | |
| } | |
| } |