Instructions to use city96/Cosmos-Predict2-14B-Text2Image-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Cosmos
How to use city96/Cosmos-Predict2-14B-Text2Image-gguf 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
- Diffusers
How to use city96/Cosmos-Predict2-14B-Text2Image-gguf with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("city96/Cosmos-Predict2-14B-Text2Image-gguf", 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
metadata
base_model: nvidia/Cosmos-Predict2-14B-Text2Image
library_name: gguf
quantized_by: city96
tags:
- nvidia
- cosmos
- diffusers
license: other
license_name: nvidia-open-model-license
license_link: >-
https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license
This is a direct GGUF conversion of nvidia/Cosmos-Predict2-14B-Text2Image.
The model files can be used in ComfyUI with the ComfyUI-GGUF custom node. Place the required model(s) in the following folders:
| Type | Name | Location | Download |
|---|---|---|---|
| Main Model | Cosmos-Predict2-14B-Text2Image | ComfyUI/models/diffusion_models |
GGUF (this repo) |
| Text Encoder | (old) T5-XXL-Encoder | ComfyUI/models/text_encoders |
Safetensors |
| VAE | Wan 2.1 VAE | ComfyUI/models/vae |
Safetensors |
Example workflow - based on the official example workflow
Example outputs - sample size of 1, not strictly representative
Notes
As this is a quantized model not a finetune, all the same restrictions/original license terms still apply.
