Instructions to use bodam/model_lora2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bodam/model_lora2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("bodam/model_lora2") prompt = "a s3f chair" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 4b738d9f6f9e52df01c56fe172ac977e3d4717e4f95a50d5d2be23e610756034
- Size of remote file:
- 1 kB
- SHA256:
- d925ef3a312cf9f1dd743e06beceb9401782b525caeac7539c0f63bd21821f45
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