Text-to-Image
Diffusers
Safetensors
Cosmos
Cosmos3OmniDiffusersPipeline
cosmos3_omni
cosmos3
quantization
int4
awq
4-bit precision
modelopt
image-to-video
Instructions to use Reza2kn/Cosmos3-Nano-INT4-AWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Reza2kn/Cosmos3-Nano-INT4-AWQ 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-INT4-AWQ", 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-INT4-AWQ 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
Download vocab.json from Reza2kn/Cosmos3-Nano-INT4-AWQ: direct link, hf CLI and curl.
- Browser
- Download file 2.78 MB
-
https://huggingface.co/Reza2kn/Cosmos3-Nano-INT4-AWQ/resolve/main/vocab.json
- Command line
-
hf download hf://Reza2kn/Cosmos3-Nano-INT4-AWQ/vocab.json
-
curl -L -o vocab.json https://huggingface.co/Reza2kn/Cosmos3-Nano-INT4-AWQ/resolve/main/vocab.json
2.78 MB
File too large to display, you can check the raw version instead.