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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 610ebde6760373d3f2436d9c0975c8b395233c93f6d32ed69186f4dc8308227e
- Size of remote file:
- 79.2 MB
- SHA256:
- 42189f0485f2c691399be6f3d4c4dd31ca389eb2c83d7f53659651ea671ce62c
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