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
- Xet hash:
- 39bd18c246a86b15fda66b94b85fcd67967f092dd0e6c08af20bf6171c8437c7
- Size of remote file:
- 10 MB
- SHA256:
- 1a30724e26f838ea23dbdbf28fa1aae1c00b979432dd9e626718e550ad3a6e95
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.