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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 401 Bytes
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"_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"
]
}
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