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main/README.md CHANGED
@@ -421,7 +421,7 @@ import torch
421
 
422
  pipe = DiffusionPipeline.from_pretrained(
423
  "CompVis/stable-diffusion-v1-4",
424
- revision='fp16',
425
  torch_dtype=torch.float16,
426
  safety_checker=None, # Very important for videos...lots of false positives while interpolating
427
  custom_pipeline="interpolate_stable_diffusion",
@@ -462,7 +462,7 @@ def download_image(url):
462
  response = requests.get(url)
463
  return PIL.Image.open(BytesIO(response.content)).convert("RGB")
464
 
465
- pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", custom_pipeline="stable_diffusion_mega", torch_dtype=torch.float16, revision="fp16")
466
  pipe.to("cuda")
467
  pipe.enable_attention_slicing()
468
 
@@ -1506,12 +1506,12 @@ scheduler = DDIMScheduler.from_pretrained("stabilityai/stable-diffusion-2-1",
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1507
  pipe = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1",
1508
  custom_pipeline="stable_diffusion_tensorrt_txt2img",
1509
- revision='fp16',
1510
  torch_dtype=torch.float16,
1511
  scheduler=scheduler,)
1512
 
1513
  # re-use cached folder to save ONNX models and TensorRT Engines
1514
- pipe.set_cached_folder("stabilityai/stable-diffusion-2-1", revision='fp16',)
1515
 
1516
  pipe = pipe.to("cuda")
1517
 
@@ -1568,7 +1568,7 @@ text_encoder = CLIPTextModel.from_pretrained(
1568
  pipeline = DiffusionPipeline.from_pretrained(
1569
  pretrained_model_name_or_path="CompVis/stable-diffusion-v1-4",
1570
  custom_pipeline="edict_pipeline",
1571
- revision="fp16",
1572
  scheduler=scheduler,
1573
  text_encoder=text_encoder,
1574
  leapfrog_steps=True,
@@ -1660,12 +1660,12 @@ scheduler = DDIMScheduler.from_pretrained("stabilityai/stable-diffusion-2-1",
1660
 
1661
  pipe = StableDiffusionImg2ImgPipeline.from_pretrained("stabilityai/stable-diffusion-2-1",
1662
  custom_pipeline="stable_diffusion_tensorrt_img2img",
1663
- revision='fp16',
1664
  torch_dtype=torch.float16,
1665
  scheduler=scheduler,)
1666
 
1667
  # re-use cached folder to save ONNX models and TensorRT Engines
1668
- pipe.set_cached_folder("stabilityai/stable-diffusion-2-1", revision='fp16',)
1669
 
1670
  pipe = pipe.to("cuda")
1671
 
@@ -2251,13 +2251,13 @@ scheduler = PNDMScheduler.from_pretrained("stabilityai/stable-diffusion-2-inpain
2251
 
2252
  pipe = StableDiffusionInpaintPipeline.from_pretrained("stabilityai/stable-diffusion-2-inpainting",
2253
  custom_pipeline="stable_diffusion_tensorrt_inpaint",
2254
- revision='fp16',
2255
  torch_dtype=torch.float16,
2256
  scheduler=scheduler,
2257
  )
2258
 
2259
  # re-use cached folder to save ONNX models and TensorRT Engines
2260
- pipe.set_cached_folder("stabilityai/stable-diffusion-2-inpainting", revision='fp16',)
2261
 
2262
  pipe = pipe.to("cuda")
2263
 
 
421
 
422
  pipe = DiffusionPipeline.from_pretrained(
423
  "CompVis/stable-diffusion-v1-4",
424
+ variant='fp16',
425
  torch_dtype=torch.float16,
426
  safety_checker=None, # Very important for videos...lots of false positives while interpolating
427
  custom_pipeline="interpolate_stable_diffusion",
 
462
  response = requests.get(url)
463
  return PIL.Image.open(BytesIO(response.content)).convert("RGB")
464
 
465
+ pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", custom_pipeline="stable_diffusion_mega", torch_dtype=torch.float16, variant="fp16")
466
  pipe.to("cuda")
467
  pipe.enable_attention_slicing()
468
 
 
1506
 
1507
  pipe = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1",
1508
  custom_pipeline="stable_diffusion_tensorrt_txt2img",
1509
+ variant='fp16',
1510
  torch_dtype=torch.float16,
1511
  scheduler=scheduler,)
1512
 
1513
  # re-use cached folder to save ONNX models and TensorRT Engines
1514
+ pipe.set_cached_folder("stabilityai/stable-diffusion-2-1", variant='fp16',)
1515
 
1516
  pipe = pipe.to("cuda")
1517
 
 
1568
  pipeline = DiffusionPipeline.from_pretrained(
1569
  pretrained_model_name_or_path="CompVis/stable-diffusion-v1-4",
1570
  custom_pipeline="edict_pipeline",
1571
+ variant="fp16",
1572
  scheduler=scheduler,
1573
  text_encoder=text_encoder,
1574
  leapfrog_steps=True,
 
1660
 
1661
  pipe = StableDiffusionImg2ImgPipeline.from_pretrained("stabilityai/stable-diffusion-2-1",
1662
  custom_pipeline="stable_diffusion_tensorrt_img2img",
1663
+ variant='fp16',
1664
  torch_dtype=torch.float16,
1665
  scheduler=scheduler,)
1666
 
1667
  # re-use cached folder to save ONNX models and TensorRT Engines
1668
+ pipe.set_cached_folder("stabilityai/stable-diffusion-2-1", variant='fp16',)
1669
 
1670
  pipe = pipe.to("cuda")
1671
 
 
2251
 
2252
  pipe = StableDiffusionInpaintPipeline.from_pretrained("stabilityai/stable-diffusion-2-inpainting",
2253
  custom_pipeline="stable_diffusion_tensorrt_inpaint",
2254
+ variant='fp16',
2255
  torch_dtype=torch.float16,
2256
  scheduler=scheduler,
2257
  )
2258
 
2259
  # re-use cached folder to save ONNX models and TensorRT Engines
2260
+ pipe.set_cached_folder("stabilityai/stable-diffusion-2-inpainting", variant='fp16',)
2261
 
2262
  pipe = pipe.to("cuda")
2263
 
main/README_community_scripts.md CHANGED
@@ -1,6 +1,6 @@
1
  # Community Scripts
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3
- **Community scripts** consist of inference examples using Diffusers pipelines that have been added by the community.
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  Please have a look at the following table to get an overview of all community examples. Click on the **Code Example** to get a copy-and-paste code example that you can try out.
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  If a community script doesn't work as expected, please open an issue and ping the author on it.
6
 
 
1
  # Community Scripts
2
 
3
+ **Community scripts** consist of inference examples using Diffusers pipelines that have been added by the community.
4
  Please have a look at the following table to get an overview of all community examples. Click on the **Code Example** to get a copy-and-paste code example that you can try out.
5
  If a community script doesn't work as expected, please open an issue and ping the author on it.
6
 
main/tiled_upscaling.py CHANGED
@@ -282,7 +282,7 @@ class StableDiffusionTiledUpscalePipeline(StableDiffusionUpscalePipeline):
282
  def main():
283
  # Run a demo
284
  model_id = "stabilityai/stable-diffusion-x4-upscaler"
285
- pipe = StableDiffusionTiledUpscalePipeline.from_pretrained(model_id, revision="fp16", torch_dtype=torch.float16)
286
  pipe = pipe.to("cuda")
287
  image = Image.open("../../docs/source/imgs/diffusers_library.jpg")
288
 
 
282
  def main():
283
  # Run a demo
284
  model_id = "stabilityai/stable-diffusion-x4-upscaler"
285
+ pipe = StableDiffusionTiledUpscalePipeline.from_pretrained(model_id, variant="fp16", torch_dtype=torch.float16)
286
  pipe = pipe.to("cuda")
287
  image = Image.open("../../docs/source/imgs/diffusers_library.jpg")
288