Instructions to use wfen/Cosmos3-Nano-FP8-Blockwise with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wfen/Cosmos3-Nano-FP8-Blockwise 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-Blockwise", 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
Commit History
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Fix LFS tracking for small text files
Blanket *.json/*.py/*.txt/*.csv/*.jinja rules forced every small config/tokenizer/script file into LFS regardless of size. Removed those rules and renormalized; text_tokenizer/tokenizer.json (11.4 MB) keeps its explicit size-justified LFS override. Large weight files are unaffected (verified: none appear in this commit's diff at all).9bf5d6a
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lm_head back to bf16
4e181f9
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initialize Blockwise FP8 quantization model
739a1f6