Hugging Face's logo

Spaces:
1inkusFace
/
StableDiffusion-3.5-Large-lora
Running on Zero

App Files Community
1
1inkusFace commited on
Commit
e05222e
·
verified ·
1 Parent(s): f1a0bd5

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +1 -4
app.py CHANGED
@@ -36,6 +36,7 @@ torch.backends.cudnn.deterministic = False
36
  torch.backends.cudnn.benchmark = False
37
  #torch.backends.cuda.preferred_blas_library="cublas"
38
  #torch.backends.cuda.preferred_linalg_library="cusolver"
 
39
 
40
  hftoken = os.getenv("HF_AUTH_TOKEN")
41
 
@@ -115,7 +116,6 @@ def infer_30(
115
  pipe.text_encoder=text_encoder #CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder', token=True).to(device=device, dtype=torch.bfloat16)
116
  pipe.text_encoder_2=text_encoder_2 #CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_2',token=True).to(device=device, dtype=torch.bfloat16)
117
  pipe.text_encoder_3=text_encoder_3 #T5EncoderModel.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_3',token=True).to(device=device, dtype=torch.bfloat16)
118
- torch.set_float32_matmul_precision("highest")
119
  seed = random.randint(0, MAX_SEED)
120
  generator = torch.Generator(device='cuda').manual_seed(seed)
121
  print('-- generating image --')
@@ -165,7 +165,6 @@ def infer_60(
165
  pipe.text_encoder=text_encoder #CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder', token=True).to(device=device, dtype=torch.bfloat16)
166
  pipe.text_encoder_2=text_encoder_2 #CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_2',token=True).to(device=device, dtype=torch.bfloat16)
167
  pipe.text_encoder_3=text_encoder_3 #T5EncoderModel.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_3',token=True).to(device=device, dtype=torch.bfloat16)
168
- torch.set_float32_matmul_precision("highest")
169
  seed = random.randint(0, MAX_SEED)
170
  generator = torch.Generator(device='cuda').manual_seed(seed)
171
  print('-- generating image --')
@@ -215,7 +214,6 @@ def infer_90(
215
  pipe.text_encoder=text_encoder #CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder', token=True).to(device=device, dtype=torch.bfloat16)
216
  pipe.text_encoder_2=text_encoder_2 #CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_2',token=True).to(device=device, dtype=torch.bfloat16)
217
  pipe.text_encoder_3=text_encoder_3 #T5EncoderModel.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_3',token=True).to(device=device, dtype=torch.bfloat16)
218
- torch.set_float32_matmul_precision("highest")
219
  seed = random.randint(0, MAX_SEED)
220
  generator = torch.Generator(device='cuda').manual_seed(seed)
221
  print('-- generating image --')
@@ -262,7 +260,6 @@ def infer_100(
262
  num_inference_steps,
263
  progress=gr.Progress(track_tqdm=True),
264
  ):
265
- torch.set_float32_matmul_precision("highest")
266
  seed = random.randint(0, MAX_SEED)
267
  generator = torch.Generator(device='cuda').manual_seed(seed)
268
  print('-- generating image --')
 
36
  torch.backends.cudnn.benchmark = False
37
  #torch.backends.cuda.preferred_blas_library="cublas"
38
  #torch.backends.cuda.preferred_linalg_library="cusolver"
39
+ torch.set_float32_matmul_precision("highest")
40
 
41
  hftoken = os.getenv("HF_AUTH_TOKEN")
42
 
 
116
  pipe.text_encoder=text_encoder #CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder', token=True).to(device=device, dtype=torch.bfloat16)
117
  pipe.text_encoder_2=text_encoder_2 #CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_2',token=True).to(device=device, dtype=torch.bfloat16)
118
  pipe.text_encoder_3=text_encoder_3 #T5EncoderModel.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_3',token=True).to(device=device, dtype=torch.bfloat16)
 
119
  seed = random.randint(0, MAX_SEED)
120
  generator = torch.Generator(device='cuda').manual_seed(seed)
121
  print('-- generating image --')
 
165
  pipe.text_encoder=text_encoder #CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder', token=True).to(device=device, dtype=torch.bfloat16)
166
  pipe.text_encoder_2=text_encoder_2 #CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_2',token=True).to(device=device, dtype=torch.bfloat16)
167
  pipe.text_encoder_3=text_encoder_3 #T5EncoderModel.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_3',token=True).to(device=device, dtype=torch.bfloat16)
 
168
  seed = random.randint(0, MAX_SEED)
169
  generator = torch.Generator(device='cuda').manual_seed(seed)
170
  print('-- generating image --')
 
214
  pipe.text_encoder=text_encoder #CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder', token=True).to(device=device, dtype=torch.bfloat16)
215
  pipe.text_encoder_2=text_encoder_2 #CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_2',token=True).to(device=device, dtype=torch.bfloat16)
216
  pipe.text_encoder_3=text_encoder_3 #T5EncoderModel.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_3',token=True).to(device=device, dtype=torch.bfloat16)
 
217
  seed = random.randint(0, MAX_SEED)
218
  generator = torch.Generator(device='cuda').manual_seed(seed)
219
  print('-- generating image --')
 
260
  num_inference_steps,
261
  progress=gr.Progress(track_tqdm=True),
262
  ):
 
263
  seed = random.randint(0, MAX_SEED)
264
  generator = torch.Generator(device='cuda').manual_seed(seed)
265
  print('-- generating image --')