Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use vishal0811/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vishal0811/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("vishal0811/output", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Ctrl+K
- checkpoint-1000
- checkpoint-1500
- checkpoint-2000
- checkpoint-2500
- checkpoint-3000
- checkpoint-3500
- checkpoint-4000
- checkpoint-500
- checkpoint-6000
- checkpoint-8000
- feature_extractor
- logs
- output_original_sample
- output_prev_sample
- safety_checker
- scheduler
- text_encoder
- tokenizer
- unet
- vae
- 1.52 kB
- 1.17 kB
- 679 Bytes