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:
- 25fb0b5f32367ee286af3b558a373e712565ce185b876c84c0e1fcd5eca68ed7
- Size of remote file:
- 6.3 GB
- SHA256:
- 472c5e4cf5056a1a59085addb5a86d801de39bf5e000d253f206a7f63c710029
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