Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use MTSAMIR/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MTSAMIR/output with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MTSAMIR/output", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of realistic blond woman" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 22bf166641d626ef3cafbfc6af600390c7ff88d3a8265b0fdb7a049686999f72
- Size of remote file:
- 3.46 GB
- SHA256:
- 1b7981fc23d95dc24d167b44cfcfb2c26e6dad68414c8daf00ab28ec11b99d92
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