Instructions to use mikesmodels/Waltz_with_Bashir_Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mikesmodels/Waltz_with_Bashir_Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mikesmodels/Waltz_with_Bashir_Diffusion", 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("mikesmodels/Waltz_with_Bashir_Diffusion", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Stable Diffusion v1.5 fine tuned on Waltz with Bashir screencaps
Use prompt: 'wltzwthbshr'
Output Samples:
Settings used: "wltzwthbshr SUBJECT", euler a, 35 steps, cfg 7, 1024x1024, high res fix on, sd-vae-ft-mse-original (AUTOMATIC1111 webui)

🧨 Diffusers
This model can be used just like any other Stable Diffusion model. For more information, please have a look at Stable diffusion Pipelines.
You can also export the model to ONNX, MPS and/or FLAX/JAX.
from diffusers import StableDiffusionPipeline
import torch
model_id = "mikesmodels/Waltz_with_Bashir_Diffusion"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")
prompt = "wltzwthbshr dwayne johnson"
image = pipe(prompt).images[0]
image.save("./dwayne_johnson.png")
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