Text-to-Image
Diffusers
Safetensors
Cosmos
Cosmos3OmniDiffusersPipeline
cosmos3_omni
cosmos3
quantization
fp8
8-bit precision
modelopt
image-to-video
Instructions to use Reza2kn/Cosmos3-Nano-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Reza2kn/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("Reza2kn/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] - Cosmos
How to use Reza2kn/Cosmos3-Nano-FP8 with Cosmos:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- bb34ea9523848ecec8f3a5d79b88d5003a703d0c825f99f09489b72802fb2273
- Size of remote file:
- 1.54 MB
- SHA256:
- b630246f9bc9bed4598b5676f4b0b688e27f68f7a10246e233c8a934e699467c
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