Instructions to use testacc1662/test-model-pubg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use testacc1662/test-model-pubg 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("testacc1662/test-model-pubg") prompt = "an image of pubgm man wearing helmet holding gun" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
LoRA DreamBooth - testacc1662/test-model-pubg
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on an image of pubgm man wearing helmet holding gun using DreamBooth. You can find some example images in the following.
LoRA for the text encoder was enabled: False.
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Model tree for testacc1662/test-model-pubg
Base model
runwayml/stable-diffusion-v1-5


