Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
landscape
classical-art
Instructions to use avuhong/DB_Monet_style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use avuhong/DB_Monet_style with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("avuhong/DB_Monet_style", dtype=torch.bfloat16, device_map="cuda") prompt = "a painting in $M## style of a fishing village under a cherry blossom forest at sunset" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vae/config.json from avuhong/DB_Monet_style: direct link, hf CLI and curl.
- Browser
- Download file 713 Bytes
-
https://huggingface.co/avuhong/DB_Monet_style/resolve/main/vae/config.json
- Command line
-
hf download hf://avuhong/DB_Monet_style/vae/config.json
-
curl -L -o config.json https://huggingface.co/avuhong/DB_Monet_style/resolve/main/vae/config.json
713 Bytes
| { | |
| "_class_name": "AutoencoderKL", | |
| "_diffusers_version": "0.10.2", | |
| "_name_or_path": "/home/avuhong/.cache/huggingface/diffusers/models--stabilityai--stable-diffusion-2-base/snapshots/f7bef89ce4f8e1ab4f3e1b4fdea0872e9d09d185/vae", | |
| "act_fn": "silu", | |
| "block_out_channels": [ | |
| 128, | |
| 256, | |
| 512, | |
| 512 | |
| ], | |
| "down_block_types": [ | |
| "DownEncoderBlock2D", | |
| "DownEncoderBlock2D", | |
| "DownEncoderBlock2D", | |
| "DownEncoderBlock2D" | |
| ], | |
| "in_channels": 3, | |
| "latent_channels": 4, | |
| "layers_per_block": 2, | |
| "norm_num_groups": 32, | |
| "out_channels": 3, | |
| "sample_size": 512, | |
| "up_block_types": [ | |
| "UpDecoderBlock2D", | |
| "UpDecoderBlock2D", | |
| "UpDecoderBlock2D", | |
| "UpDecoderBlock2D" | |
| ] | |
| } | |