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:
- f22b4a798c1c64901ec965918dd4faff93e5a64b354cd2197507ace71d8f8f89
- Size of remote file:
- 4.47 kB
- SHA256:
- cd53d72d362dd9abe6f46313f83dc86ffefb43a1a0aaaa495877870c89a17edc
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