Text-to-Image
Diffusers
TensorBoard
lora
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use dsgesd32/lora-trained-sd2-chim-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dsgesd32/lora-trained-sd2-chim-2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Manojb/stable-diffusion-2-base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("dsgesd32/lora-trained-sd2-chim-2") prompt = "a photo of sks person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- 25aa459ba48f1c20d08932dfe86f264c6f5b9d911db03ae0aceec2c8a577a836
- Size of remote file:
- 308 kB
- SHA256:
- 9031caed98a45e1414a049bdf67f428222997a60a9e2d7822f0d214f584266ce
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