Instructions to use fusing/latent-diffusion-text2im-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fusing/latent-diffusion-text2im-large with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fusing/latent-diffusion-text2im-large", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_class_name": "LDMTextToImagePipeline", | |
| "_diffusers_version": "0.0.1", | |
| "_module": "latent_diffusion", | |
| "bert": [ | |
| "latent_diffusion", | |
| "LDMBertModel" | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "DDIMScheduler" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "BertTokenizer" | |
| ], | |
| "unet": [ | |
| "diffusers", | |
| "UNetLDMModel" | |
| ], | |
| "vqvae": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ] | |
| } | |