Instructions to use recky101/new_l_cfld_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use recky101/new_l_cfld_model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("recky101/new_l_cfld_model", 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:
- a6bb380cdb1f8bb3978851ca10e8d3e0cd88125f09e6e296a5f40a0a91488b6f
- Size of remote file:
- 630 Bytes
- SHA256:
- 2f865644a8f93b755c0bd641002594a3a9293de98b92906845eedffa623256b2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.