Instructions to use jinofcoolnes/corporate_memphis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jinofcoolnes/corporate_memphis with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jinofcoolnes/corporate_memphis", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("jinofcoolnes/corporate_memphis", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Corporate Memphis is a finetuned Stable Diffusion model by @jinofcoolnes
Use prompt: 'Corporate_Memphis digital illustration'
𧨠Diffusers
This model can be used just like any other Stable Diffusion model. For more information, please have a look at the Stable Diffusion documentation.
You can also export the model to ONNX, MPS and/or FLAX/JAX.
from diffusers import StableDiffusionPipeline
import torch
model_id = "jinofcoolnes/corporate_memphis"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")
prompt = "coliseum full of different cars with different colors and shapes; Corporate_Memphis digital illustration"
image = pipe(prompt).images[0]
image.save("./cars.png")
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