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| author | Volpeon <git@volpeon.ink> | 2022-10-13 09:45:27 +0200 |
|---|---|---|
| committer | Volpeon <git@volpeon.ink> | 2022-10-13 09:45:27 +0200 |
| commit | db0996c299fdd559ebf9cd48f9dbe47474ed7b07 (patch) | |
| tree | 0d306c661ed5629e7d69566a82d588aca5ed86a9 /infer.py | |
| parent | Various updates (diff) | |
| download | textual-inversion-diff-db0996c299fdd559ebf9cd48f9dbe47474ed7b07.tar.gz textual-inversion-diff-db0996c299fdd559ebf9cd48f9dbe47474ed7b07.tar.bz2 textual-inversion-diff-db0996c299fdd559ebf9cd48f9dbe47474ed7b07.zip | |
Added TI+Dreambooth training
Diffstat (limited to 'infer.py')
| -rw-r--r-- | infer.py | 8 |
1 files changed, 4 insertions, 4 deletions
| @@ -205,10 +205,10 @@ def load_embeddings(tokenizer, text_encoder, embeddings_dir): | |||
| 205 | def create_pipeline(model, scheduler, embeddings_dir, dtype): | 205 | def create_pipeline(model, scheduler, embeddings_dir, dtype): |
| 206 | print("Loading Stable Diffusion pipeline...") | 206 | print("Loading Stable Diffusion pipeline...") |
| 207 | 207 | ||
| 208 | tokenizer = CLIPTokenizer.from_pretrained(model, subfolder='/tokenizer', torch_dtype=dtype) | 208 | tokenizer = CLIPTokenizer.from_pretrained(model, subfolder='tokenizer', torch_dtype=dtype) |
| 209 | text_encoder = CLIPTextModel.from_pretrained(model, subfolder='/text_encoder', torch_dtype=dtype) | 209 | text_encoder = CLIPTextModel.from_pretrained(model, subfolder='text_encoder', torch_dtype=dtype) |
| 210 | vae = AutoencoderKL.from_pretrained(model, subfolder='/vae', torch_dtype=dtype) | 210 | vae = AutoencoderKL.from_pretrained(model, subfolder='vae', torch_dtype=dtype) |
| 211 | unet = UNet2DConditionModel.from_pretrained(model, subfolder='/unet', torch_dtype=dtype) | 211 | unet = UNet2DConditionModel.from_pretrained(model, subfolder='unet', torch_dtype=dtype) |
| 212 | 212 | ||
| 213 | load_embeddings(tokenizer, text_encoder, embeddings_dir) | 213 | load_embeddings(tokenizer, text_encoder, embeddings_dir) |
| 214 | 214 | ||