Instructions to use sijunhe/tiny-random-stable-diffusion-pipe-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- paddlenlp
How to use sijunhe/tiny-random-stable-diffusion-pipe-1 with paddlenlp:
# ⚠️ Type of model unknown from paddlenlp.transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sijunhe/tiny-random-stable-diffusion-pipe-1", from_hf_hub=True) model = AutoModel.from_pretrained("sijunhe/tiny-random-stable-diffusion-pipe-1", from_hf_hub=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "_class_name": "AutoencoderKL", | |
| "_diffusers_version": "0.4.0.dev0", | |
| "_ppdiffusers_version": "0.0.0", | |
| "act_fn": "silu", | |
| "block_out_channels": [ | |
| 32, | |
| 64 | |
| ], | |
| "down_block_types": [ | |
| "DownEncoderBlock2D", | |
| "DownEncoderBlock2D" | |
| ], | |
| "in_channels": 3, | |
| "latent_channels": 4, | |
| "layers_per_block": 1, | |
| "norm_num_groups": 32, | |
| "out_channels": 3, | |
| "sample_size": 32, | |
| "up_block_types": [ | |
| "UpDecoderBlock2D", | |
| "UpDecoderBlock2D" | |
| ] | |
| } | |