Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
diffusers-training
lora
Instructions to use ahbpp/ham10000-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ahbpp/ham10000-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ahbpp/ham10000-lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 412da276a3b3c0a02482912ce6842982649d56612eafd94edfcca8ee3e6a1d3e
- Size of remote file:
- 346 kB
- SHA256:
- d96338e3276e8045da2e52b2983227ffdd8bbef9961782b7f62da470adb3c3d5
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