diff options
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 | ||