Instructions to use shalpin87/diffusion_conditional with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use shalpin87/diffusion_conditional with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("shalpin87/diffusion_conditional", 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
Download unet/config.json from shalpin87/diffusion_conditional: direct link, hf CLI and curl.
- Browser
- Download file 865 Bytes
-
https://huggingface.co/shalpin87/diffusion_conditional/resolve/main/unet/config.json
- Command line
-
hf download hf://shalpin87/diffusion_conditional/unet/config.json
-
curl -L -o config.json https://huggingface.co/shalpin87/diffusion_conditional/resolve/main/unet/config.json
865 Bytes
| { | |
| "_class_name": "UNet2DConditionModel", | |
| "_diffusers_version": "0.1.3", | |
| "_name_or_path": "/root/.cache/huggingface/diffusers/models--shalpin87--diffusion_conditional/snapshots/88e0844f6fa1682e073320f94bb2f1139a40955e/unet", | |
| "act_fn": "silu", | |
| "attention_head_dim": 8, | |
| "block_out_channels": [ | |
| 128, | |
| 128, | |
| 256, | |
| 256 | |
| ], | |
| "center_input_sample": false, | |
| "down_block_types": [ | |
| "CrossAttnDownBlock2D", | |
| "CrossAttnDownBlock2D", | |
| "CrossAttnDownBlock2D", | |
| "DownBlock2D" | |
| ], | |
| "downsample_padding": 1, | |
| "flip_sin_to_cos": true, | |
| "freq_shift": 0, | |
| "in_channels": 3, | |
| "layers_per_block": 2, | |
| "mid_block_scale_factor": 1, | |
| "norm_eps": 1e-05, | |
| "norm_num_groups": 32, | |
| "out_channels": 3, | |
| "sample_size": 32, | |
| "up_block_types": [ | |
| "UpBlock2D", | |
| "CrossAttnUpBlock2D", | |
| "CrossAttnUpBlock2D", | |
| "CrossAttnUpBlock2D" | |
| ] | |
| } | |