diff options
Diffstat (limited to 'infer.py')
| -rw-r--r-- | infer.py | 4 |
1 files changed, 2 insertions, 2 deletions
| @@ -34,7 +34,7 @@ torch.backends.cudnn.benchmark = True | |||
| 34 | default_args = { | 34 | default_args = { |
| 35 | "model": "stabilityai/stable-diffusion-2-1", | 35 | "model": "stabilityai/stable-diffusion-2-1", |
| 36 | "precision": "fp32", | 36 | "precision": "fp32", |
| 37 | "ti_embeddings_dir": "embeddings_ti", | 37 | "ti_embeddings_dir": "embeddings", |
| 38 | "output_dir": "output/inference", | 38 | "output_dir": "output/inference", |
| 39 | "config": None, | 39 | "config": None, |
| 40 | } | 40 | } |
| @@ -190,7 +190,7 @@ def create_pipeline(model, embeddings_dir, dtype): | |||
| 190 | unet = UNet2DConditionModel.from_pretrained(model, subfolder='unet', torch_dtype=dtype) | 190 | unet = UNet2DConditionModel.from_pretrained(model, subfolder='unet', torch_dtype=dtype) |
| 191 | scheduler = DDIMScheduler.from_pretrained(model, subfolder='scheduler', torch_dtype=dtype) | 191 | scheduler = DDIMScheduler.from_pretrained(model, subfolder='scheduler', torch_dtype=dtype) |
| 192 | 192 | ||
| 193 | added_tokens = load_text_embeddings(tokenizer, text_encoder, embeddings_dir) | 193 | added_tokens = load_text_embeddings(tokenizer, text_encoder, Path(embeddings_dir)) |
| 194 | print(f"Added {len(added_tokens)} tokens from embeddings dir: {added_tokens}") | 194 | print(f"Added {len(added_tokens)} tokens from embeddings dir: {added_tokens}") |
| 195 | 195 | ||
| 196 | pipeline = VlpnStableDiffusion( | 196 | pipeline = VlpnStableDiffusion( |
