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:
- c39bdefe04614239556529691c2ed06d7aeefea7a1d8783fe01a8348cdc7d9f5
- Size of remote file:
- 9.95 GB
- SHA256:
- 6d211f1c14cd793156da3a840dd5462ae072046fcd6f1dc64c613a5343bfe896
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