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
Download quantizer_map_diff.json from wfen/Cosmos3-Nano-FP8: direct link, hf CLI and curl.
- Browser
- Download file 366 Bytes
-
https://huggingface.co/wfen/Cosmos3-Nano-FP8/resolve/main/quantizer_map_diff.json
- Command line
-
hf download hf://wfen/Cosmos3-Nano-FP8/quantizer_map_diff.json
-
curl -L -o quantizer_map_diff.json https://huggingface.co/wfen/Cosmos3-Nano-FP8/resolve/main/quantizer_map_diff.json
366 Bytes
| { | |
| "n_weight_quantized": 505, | |
| "expected_quantized_count": 505, | |
| "inv2_diff_empty": true, | |
| "unexpectedly_quantized": [], | |
| "unexpectedly_bf16": [], | |
| "wrong_mode": [], | |
| "dropped_action_keys": [ | |
| "action_modality_embed", | |
| "action_proj_in.bias.weight", | |
| "action_proj_in.fc.weight", | |
| "action_proj_out.bias.weight", | |
| "action_proj_out.fc.weight" | |
| ] | |
| } |