Instructions to use lfernandopg/mach-5-model-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lfernandopg/mach-5-model-v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lfernandopg/mach-5-model-v1", 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 Settings
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("lfernandopg/mach-5-model-v1", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Mach 5 on Stable Diffusion
This is the <mach-5> concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the Stable Conceptualizer notebook.
Here is the new concept you will be able to use as an object:

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Model tree for lfernandopg/mach-5-model-v1
Base model
stabilityai/stable-diffusion-2