Instructions to use xgemstarx/hope_grey_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xgemstarx/hope_grey_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("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("xgemstarx/hope_grey_model") prompt = "a photo of xjhopex" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- a1d3ad9fba90e254a8f91846233956098b4413783387017ba9a5b5147944eafe
- Size of remote file:
- 79.2 MB
- SHA256:
- 70b11fbf73e1f2c40a6e6e6ca6ad1abbf70c3259e00c4b468d0516b17330b3e6
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