Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
textual_inversion
diffusers-training
lora
template:sd-lora
sd3
sd3-diffusers
Instructions to use SidXXD/m-213 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/m-213 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("SidXXD/m-213") 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:
- 8d2af2e884a5da2908b395ac0ee34bf97480aa0a6809414b1966fe8883516d3f
- Size of remote file:
- 4.47 kB
- SHA256:
- 11a345faeb29a0130c49eebc7e3f6705920dab6a51872f5bdd5c3413b580a243
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