Text-to-Image
Diffusers
PyTorch
Safetensors
English
StableDiffusionPipeline
diffusion
ddpm
custom-architecture
Instructions to use lea97338/Lou with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lea97338/Lou with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lea97338/Lou", 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
Download model_index.json from lea97338/Lou: direct link, hf CLI and curl.
- Browser
- Download file 371 Bytes
-
https://huggingface.co/lea97338/Lou/resolve/main/model_index.json
- Command line
-
hf download hf://lea97338/Lou/model_index.json
-
curl -L -o model_index.json https://huggingface.co/lea97338/Lou/resolve/main/model_index.json
371 Bytes
| {"_class_name": "StableDiffusionPipeline", "_diffusers_version": "0.21.4", "scheduler": ["diffusers", "DDPMScheduler"], "text_encoder": ["transformers", "CLIPTextModel"], "tokenizer": ["transformers", "CLIPTokenizer"], "unet": ["diffusers", "UNet2DConditionModel"], "vae": ["diffusers", "AutoencoderKL"], "feature_extractor": [null, null], "safety_checker": [null, null]} |