a few fix for SingleFile tests (#9522)

* update sd15 repo

* update more

src/diffusers/loaders/single_file_utils.py

@@ -14,6 +14,7 @@
 # limitations under the License.
 """Conversion script for the Stable Diffusion checkpoints."""
 
+import copy
 import os
 import re
 from contextlib import nullcontext
@@ -91,11 +92,11 @@ DIFFUSERS_DEFAULT_PIPELINE_PATHS = {
     "xl_inpaint": {"pretrained_model_name_or_path": "diffusers/stable-diffusion-xl-1.0-inpainting-0.1"},
     "playground-v2-5": {"pretrained_model_name_or_path": "playgroundai/playground-v2.5-1024px-aesthetic"},
     "upscale": {"pretrained_model_name_or_path": "stabilityai/stable-diffusion-x4-upscaler"},
-    "inpainting": {"pretrained_model_name_or_path": "Lykon/dreamshaper-8-inpainting"},
+    "inpainting": {"pretrained_model_name_or_path": "stable-diffusion-v1-5/stable-diffusion-inpainting"},
     "inpainting_v2": {"pretrained_model_name_or_path": "stabilityai/stable-diffusion-2-inpainting"},
     "controlnet": {"pretrained_model_name_or_path": "lllyasviel/control_v11p_sd15_canny"},
     "v2": {"pretrained_model_name_or_path": "stabilityai/stable-diffusion-2-1"},
-    "v1": {"pretrained_model_name_or_path": "Lykon/dreamshaper-8"},
+    "v1": {"pretrained_model_name_or_path": "stable-diffusion-v1-5/stable-diffusion-v1-5"},
     "stable_cascade_stage_b": {"pretrained_model_name_or_path": "stabilityai/stable-cascade", "subfolder": "decoder"},
     "stable_cascade_stage_b_lite": {
         "pretrained_model_name_or_path": "stabilityai/stable-cascade",
@@ -541,6 +542,7 @@ def infer_diffusers_model_type(checkpoint):
 def fetch_diffusers_config(checkpoint):
     model_type = infer_diffusers_model_type(checkpoint)
     model_path = DIFFUSERS_DEFAULT_PIPELINE_PATHS[model_type]
+    model_path = copy.deepcopy(model_path)
 
     return model_path
 

tests/lora/test_lora_layers_sd.py

@@ -102,7 +102,7 @@ class StableDiffusionLoRATests(PeftLoraLoaderMixinTests, unittest.TestCase):
     @slow
     @require_torch_gpu
     def test_integration_move_lora_cpu(self):
-        path = "Jiali/stable-diffusion-1.5"
+        path = "stable-diffusion-v1-5/stable-diffusion-v1-5"
         lora_id = "takuma104/lora-test-text-encoder-lora-target"
 
         pipe = StableDiffusionPipeline.from_pretrained(path, torch_dtype=torch.float16)
@@ -161,7 +161,7 @@ class StableDiffusionLoRATests(PeftLoraLoaderMixinTests, unittest.TestCase):
     def test_integration_move_lora_dora_cpu(self):
         from peft import LoraConfig
 
-        path = "Jiali/stable-diffusion-1.5"
+        path = "stable-diffusion-v1-5/stable-diffusion-v1-5"
         unet_lora_config = LoraConfig(
             init_lora_weights="gaussian",
             target_modules=["to_k", "to_q", "to_v", "to_out.0"],
@@ -221,7 +221,7 @@ class LoraIntegrationTests(unittest.TestCase):
         torch.cuda.empty_cache()
 
     def test_integration_logits_with_scale(self):
-        path = "Jiali/stable-diffusion-1.5"
+        path = "stable-diffusion-v1-5/stable-diffusion-v1-5"
         lora_id = "takuma104/lora-test-text-encoder-lora-target"
 
         pipe = StableDiffusionPipeline.from_pretrained(path, torch_dtype=torch.float32)
@@ -253,7 +253,7 @@ class LoraIntegrationTests(unittest.TestCase):
         release_memory(pipe)
 
     def test_integration_logits_no_scale(self):
-        path = "Jiali/stable-diffusion-1.5"
+        path = "stable-diffusion-v1-5/stable-diffusion-v1-5"
         lora_id = "takuma104/lora-test-text-encoder-lora-target"
 
         pipe = StableDiffusionPipeline.from_pretrained(path, torch_dtype=torch.float32)
@@ -284,7 +284,7 @@ class LoraIntegrationTests(unittest.TestCase):
 
         lora_model_id = "hf-internal-testing/lora_dreambooth_dog_example"
 
-        base_model_id = "Jiali/stable-diffusion-1.5"
+        base_model_id = "stable-diffusion-v1-5/stable-diffusion-v1-5"
 
         pipe = StableDiffusionPipeline.from_pretrained(base_model_id, safety_checker=None)
         pipe = pipe.to(torch_device)
@@ -308,7 +308,7 @@ class LoraIntegrationTests(unittest.TestCase):
 
         lora_model_id = "hf-internal-testing/lora-trained"
 
-        base_model_id = "Jiali/stable-diffusion-1.5"
+        base_model_id = "stable-diffusion-v1-5/stable-diffusion-v1-5"
 
         pipe = StableDiffusionPipeline.from_pretrained(base_model_id, safety_checker=None)
         pipe = pipe.to(torch_device)
@@ -419,9 +419,9 @@ class LoraIntegrationTests(unittest.TestCase):
     def test_kohya_sd_v15_with_higher_dimensions(self):
         generator = torch.Generator().manual_seed(0)
 
-        pipe = StableDiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5", safety_checker=None).to(
-            torch_device
-        )
+        pipe = StableDiffusionPipeline.from_pretrained(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None
+        ).to(torch_device)
         lora_model_id = "hf-internal-testing/urushisato-lora"
         lora_filename = "urushisato_v15.safetensors"
         pipe.load_lora_weights(lora_model_id, weight_name=lora_filename)
@@ -444,7 +444,7 @@ class LoraIntegrationTests(unittest.TestCase):
 
         lora_model_id = "hf-internal-testing/sd-model-finetuned-lora-t4"
 
-        base_model_id = "Jiali/stable-diffusion-1.5"
+        base_model_id = "stable-diffusion-v1-5/stable-diffusion-v1-5"
 
         pipe = StableDiffusionPipeline.from_pretrained(base_model_id, safety_checker=None)
         pipe = pipe.to(torch_device)
@@ -467,9 +467,9 @@ class LoraIntegrationTests(unittest.TestCase):
         prompt = "masterpiece, best quality, mountain"
         num_inference_steps = 2
 
-        pipe = StableDiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5", safety_checker=None).to(
-            torch_device
-        )
+        pipe = StableDiffusionPipeline.from_pretrained(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None
+        ).to(torch_device)
         initial_images = pipe(
             prompt, output_type="np", generator=generator, num_inference_steps=num_inference_steps
         ).images
@@ -505,9 +505,9 @@ class LoraIntegrationTests(unittest.TestCase):
         prompt = "masterpiece, best quality, mountain"
         num_inference_steps = 2
 
-        pipe = StableDiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5", safety_checker=None).to(
-            torch_device
-        )
+        pipe = StableDiffusionPipeline.from_pretrained(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None
+        ).to(torch_device)
         initial_images = pipe(
             prompt, output_type="np", generator=generator, num_inference_steps=num_inference_steps
         ).images
@@ -547,9 +547,9 @@ class LoraIntegrationTests(unittest.TestCase):
 
     def test_not_empty_state_dict(self):
         # Makes sure https://github.com/huggingface/diffusers/issues/7054 does not happen again
-        pipe = AutoPipelineForText2Image.from_pretrained("Jiali/stable-diffusion-1.5", torch_dtype=torch.float16).to(
-            torch_device
-        )
+        pipe = AutoPipelineForText2Image.from_pretrained(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.float16
+        ).to(torch_device)
         pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
 
         cached_file = hf_hub_download("hf-internal-testing/lcm-lora-test-sd-v1-5", "test_lora.safetensors")
@@ -561,9 +561,9 @@ class LoraIntegrationTests(unittest.TestCase):
 
     def test_load_unload_load_state_dict(self):
         # Makes sure https://github.com/huggingface/diffusers/issues/7054 does not happen again
-        pipe = AutoPipelineForText2Image.from_pretrained("Jiali/stable-diffusion-1.5", torch_dtype=torch.float16).to(
-            torch_device
-        )
+        pipe = AutoPipelineForText2Image.from_pretrained(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.float16
+        ).to(torch_device)
         pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
 
         cached_file = hf_hub_download("hf-internal-testing/lcm-lora-test-sd-v1-5", "test_lora.safetensors")
@@ -580,7 +580,9 @@ class LoraIntegrationTests(unittest.TestCase):
         release_memory(pipe)
 
     def test_sdv1_5_lcm_lora(self):
-        pipe = DiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5", torch_dtype=torch.float16)
+        pipe = DiffusionPipeline.from_pretrained(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.float16
+        )
         pipe.to(torch_device)
         pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
 
@@ -608,7 +610,9 @@ class LoraIntegrationTests(unittest.TestCase):
         release_memory(pipe)
 
     def test_sdv1_5_lcm_lora_img2img(self):
-        pipe = AutoPipelineForImage2Image.from_pretrained("Jiali/stable-diffusion-1.5", torch_dtype=torch.float16)
+        pipe = AutoPipelineForImage2Image.from_pretrained(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.float16
+        )
         pipe.to(torch_device)
         pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
 
@@ -649,7 +653,7 @@ class LoraIntegrationTests(unittest.TestCase):
         This test simply checks that loading a LoRA with an empty network alpha works fine
         See: https://github.com/huggingface/diffusers/issues/5606
         """
-        pipeline = StableDiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5")
+        pipeline = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
         pipeline.enable_sequential_cpu_offload()
         civitai_path = hf_hub_download("ybelkada/test-ahi-civitai", "ahi_lora_weights.safetensors")
         pipeline.load_lora_weights(civitai_path, adapter_name="ahri")

tests/models/autoencoders/test_models_vae.py

@@ -1051,7 +1051,9 @@ class ConsistencyDecoderVAEIntegrationTests(unittest.TestCase):
 
     def test_sd(self):
         vae = ConsistencyDecoderVAE.from_pretrained("openai/consistency-decoder")  # TODO - update
-        pipe = StableDiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5", vae=vae, safety_checker=None)
+        pipe = StableDiffusionPipeline.from_pretrained(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", vae=vae, safety_checker=None
+        )
         pipe.to(torch_device)
 
         out = pipe(
@@ -1099,7 +1101,7 @@ class ConsistencyDecoderVAEIntegrationTests(unittest.TestCase):
             "openai/consistency-decoder", torch_dtype=torch.float16
         )  # TODO - update
         pipe = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5",
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
             torch_dtype=torch.float16,
             vae=vae,
             safety_checker=None,
@@ -1124,7 +1126,7 @@ class ConsistencyDecoderVAEIntegrationTests(unittest.TestCase):
     def test_vae_tiling(self):
         vae = ConsistencyDecoderVAE.from_pretrained("openai/consistency-decoder", torch_dtype=torch.float16)
         pipe = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", vae=vae, safety_checker=None, torch_dtype=torch.float16
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", vae=vae, safety_checker=None, torch_dtype=torch.float16
         )
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)

tests/pipelines/controlnet/test_controlnet.py

@@ -73,7 +73,7 @@ def _test_stable_diffusion_compile(in_queue, out_queue, timeout):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-canny")
 
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.to("cuda")
         pipe.set_progress_bar_config(disable=None)
@@ -715,7 +715,7 @@ class ControlNetPipelineSlowTests(unittest.TestCase):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-canny")
 
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.enable_model_cpu_offload()
         pipe.set_progress_bar_config(disable=None)
@@ -742,7 +742,7 @@ class ControlNetPipelineSlowTests(unittest.TestCase):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-depth")
 
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.enable_model_cpu_offload()
         pipe.set_progress_bar_config(disable=None)
@@ -769,7 +769,7 @@ class ControlNetPipelineSlowTests(unittest.TestCase):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-hed")
 
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.enable_model_cpu_offload()
         pipe.set_progress_bar_config(disable=None)
@@ -796,7 +796,7 @@ class ControlNetPipelineSlowTests(unittest.TestCase):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-mlsd")
 
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.enable_model_cpu_offload()
         pipe.set_progress_bar_config(disable=None)
@@ -823,7 +823,7 @@ class ControlNetPipelineSlowTests(unittest.TestCase):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-normal")
 
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.enable_model_cpu_offload()
         pipe.set_progress_bar_config(disable=None)
@@ -850,7 +850,7 @@ class ControlNetPipelineSlowTests(unittest.TestCase):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-openpose")
 
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.enable_model_cpu_offload()
         pipe.set_progress_bar_config(disable=None)
@@ -877,7 +877,7 @@ class ControlNetPipelineSlowTests(unittest.TestCase):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-scribble")
 
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.enable_model_cpu_offload()
         pipe.set_progress_bar_config(disable=None)
@@ -904,7 +904,7 @@ class ControlNetPipelineSlowTests(unittest.TestCase):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-seg")
 
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.enable_model_cpu_offload()
         pipe.set_progress_bar_config(disable=None)
@@ -935,7 +935,7 @@ class ControlNetPipelineSlowTests(unittest.TestCase):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-seg")
 
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.set_progress_bar_config(disable=None)
         pipe.enable_attention_slicing()
@@ -961,7 +961,7 @@ class ControlNetPipelineSlowTests(unittest.TestCase):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-canny")
 
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.enable_model_cpu_offload()
         pipe.set_progress_bar_config(disable=None)
@@ -993,7 +993,7 @@ class ControlNetPipelineSlowTests(unittest.TestCase):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-canny")
 
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config)
         pipe.enable_model_cpu_offload()
@@ -1035,7 +1035,7 @@ class ControlNetPipelineSlowTests(unittest.TestCase):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/control_v11e_sd15_shuffle")
 
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.enable_model_cpu_offload()
         pipe.set_progress_bar_config(disable=None)
@@ -1081,7 +1081,9 @@ class StableDiffusionMultiControlNetPipelineSlowTests(unittest.TestCase):
         controlnet_pose = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-openpose")
 
         pipe = StableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=[controlnet_pose, controlnet_canny]
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
+            safety_checker=None,
+            controlnet=[controlnet_pose, controlnet_canny],
         )
         pipe.enable_model_cpu_offload()
         pipe.set_progress_bar_config(disable=None)

tests/pipelines/controlnet/test_controlnet_img2img.py

@@ -407,7 +407,7 @@ class ControlNetImg2ImgPipelineSlowTests(unittest.TestCase):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-canny")
 
         pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.enable_model_cpu_offload()
         pipe.set_progress_bar_config(disable=None)

tests/pipelines/controlnet/test_controlnet_inpaint.py

@@ -504,7 +504,7 @@ class ControlNetInpaintPipelineSlowTests(unittest.TestCase):
         controlnet = ControlNetModel.from_pretrained("lllyasviel/control_v11p_sd15_inpaint")
 
         pipe = StableDiffusionControlNetInpaintPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, controlnet=controlnet
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, controlnet=controlnet
         )
         pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
         pipe.enable_model_cpu_offload()

tests/pipelines/controlnet/test_flax_controlnet.py

@@ -41,7 +41,7 @@ class FlaxControlNetPipelineIntegrationTests(unittest.TestCase):
             "lllyasviel/sd-controlnet-canny", from_pt=True, dtype=jnp.bfloat16
         )
         pipe, params = FlaxStableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", controlnet=controlnet, from_pt=True, dtype=jnp.bfloat16
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", controlnet=controlnet, from_pt=True, dtype=jnp.bfloat16
         )
         params["controlnet"] = controlnet_params
 
@@ -86,7 +86,7 @@ class FlaxControlNetPipelineIntegrationTests(unittest.TestCase):
             "lllyasviel/sd-controlnet-openpose", from_pt=True, dtype=jnp.bfloat16
         )
         pipe, params = FlaxStableDiffusionControlNetPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", controlnet=controlnet, from_pt=True, dtype=jnp.bfloat16
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", controlnet=controlnet, from_pt=True, dtype=jnp.bfloat16
         )
         params["controlnet"] = controlnet_params
 

tests/pipelines/ip_adapters/test_ip_adapter_stable_diffusion.py

@@ -170,7 +170,10 @@ class IPAdapterSDIntegrationTests(IPAdapterNightlyTestsMixin):
     def test_text_to_image(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
         pipeline = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", image_encoder=image_encoder, safety_checker=None, torch_dtype=self.dtype
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
+            image_encoder=image_encoder,
+            safety_checker=None,
+            torch_dtype=self.dtype,
         )
         pipeline.to(torch_device)
         pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter_sd15.bin")
@@ -200,7 +203,10 @@ class IPAdapterSDIntegrationTests(IPAdapterNightlyTestsMixin):
     def test_image_to_image(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
         pipeline = StableDiffusionImg2ImgPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", image_encoder=image_encoder, safety_checker=None, torch_dtype=self.dtype
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
+            image_encoder=image_encoder,
+            safety_checker=None,
+            torch_dtype=self.dtype,
         )
         pipeline.to(torch_device)
         pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter_sd15.bin")
@@ -232,7 +238,10 @@ class IPAdapterSDIntegrationTests(IPAdapterNightlyTestsMixin):
     def test_inpainting(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
         pipeline = StableDiffusionInpaintPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", image_encoder=image_encoder, safety_checker=None, torch_dtype=self.dtype
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
+            image_encoder=image_encoder,
+            safety_checker=None,
+            torch_dtype=self.dtype,
         )
         pipeline.to(torch_device)
         pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter_sd15.bin")
@@ -260,7 +269,10 @@ class IPAdapterSDIntegrationTests(IPAdapterNightlyTestsMixin):
     def test_text_to_image_model_cpu_offload(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
         pipeline = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", image_encoder=image_encoder, safety_checker=None, torch_dtype=self.dtype
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
+            image_encoder=image_encoder,
+            safety_checker=None,
+            torch_dtype=self.dtype,
         )
         pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter_sd15.bin")
         pipeline.to(torch_device)
@@ -287,7 +299,10 @@ class IPAdapterSDIntegrationTests(IPAdapterNightlyTestsMixin):
     def test_text_to_image_full_face(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
         pipeline = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", image_encoder=image_encoder, safety_checker=None, torch_dtype=self.dtype
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
+            image_encoder=image_encoder,
+            safety_checker=None,
+            torch_dtype=self.dtype,
         )
         pipeline.to(torch_device)
         pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter-full-face_sd15.bin")
@@ -304,7 +319,10 @@ class IPAdapterSDIntegrationTests(IPAdapterNightlyTestsMixin):
     def test_unload(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
         pipeline = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", image_encoder=image_encoder, safety_checker=None, torch_dtype=self.dtype
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
+            image_encoder=image_encoder,
+            safety_checker=None,
+            torch_dtype=self.dtype,
         )
         before_processors = [attn_proc.__class__ for attn_proc in pipeline.unet.attn_processors.values()]
         pipeline.to(torch_device)
@@ -323,7 +341,10 @@ class IPAdapterSDIntegrationTests(IPAdapterNightlyTestsMixin):
     def test_multi(self):
         image_encoder = self.get_image_encoder(repo_id="h94/IP-Adapter", subfolder="models/image_encoder")
         pipeline = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", image_encoder=image_encoder, safety_checker=None, torch_dtype=self.dtype
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
+            image_encoder=image_encoder,
+            safety_checker=None,
+            torch_dtype=self.dtype,
         )
         pipeline.to(torch_device)
         pipeline.load_ip_adapter(
@@ -343,7 +364,7 @@ class IPAdapterSDIntegrationTests(IPAdapterNightlyTestsMixin):
 
     def test_text_to_image_face_id(self):
         pipeline = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, torch_dtype=self.dtype
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, torch_dtype=self.dtype
         )
         pipeline.to(torch_device)
         pipeline.load_ip_adapter(

tests/pipelines/ledits_pp/test_ledits_pp_stable_diffusion.py

@@ -224,7 +224,7 @@ class LEditsPPPipelineStableDiffusionSlowTests(unittest.TestCase):
 
     def test_ledits_pp_editing(self):
         pipe = LEditsPPPipelineStableDiffusion.from_pretrained(
-            "Jiali/stable-diffusion-1.5", safety_checker=None, torch_dtype=torch.float16
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None, torch_dtype=torch.float16
         )
         pipe = pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)

tests/pipelines/pag/test_pag_sd.py

@@ -283,7 +283,7 @@ class StableDiffusionPAGPipelineFastTests(
 @require_torch_gpu
 class StableDiffusionPAGPipelineIntegrationTests(unittest.TestCase):
     pipeline_class = StableDiffusionPAGPipeline
-    repo_id = "Jiali/stable-diffusion-1.5"
+    repo_id = "stable-diffusion-v1-5/stable-diffusion-v1-5"
 
     def setUp(self):
         super().setUp()

tests/pipelines/semantic_stable_diffusion/test_semantic_diffusion.py

@@ -287,7 +287,7 @@ class SemanticDiffusionPipelineIntegrationTests(unittest.TestCase):
 
     def test_positive_guidance(self):
         torch_device = "cuda"
-        pipe = StableDiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5")
+        pipe = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
         pipe = pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
 
@@ -370,7 +370,7 @@ class SemanticDiffusionPipelineIntegrationTests(unittest.TestCase):
 
     def test_negative_guidance(self):
         torch_device = "cuda"
-        pipe = StableDiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5")
+        pipe = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
         pipe = pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
 
@@ -453,7 +453,7 @@ class SemanticDiffusionPipelineIntegrationTests(unittest.TestCase):
 
     def test_multi_cond_guidance(self):
         torch_device = "cuda"
-        pipe = StableDiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5")
+        pipe = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
         pipe = pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
 
@@ -536,7 +536,9 @@ class SemanticDiffusionPipelineIntegrationTests(unittest.TestCase):
 
     def test_guidance_fp16(self):
         torch_device = "cuda"
-        pipe = StableDiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5", torch_dtype=torch.float16)
+        pipe = StableDiffusionPipeline.from_pretrained(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.float16
+        )
         pipe = pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
 

tests/pipelines/stable_diffusion/test_onnx_stable_diffusion.py

@@ -250,10 +250,10 @@ class OnnxStableDiffusionPipelineIntegrationTests(unittest.TestCase):
 
     def test_inference_ddim(self):
         ddim_scheduler = DDIMScheduler.from_pretrained(
-            "Jiali/stable-diffusion-1.5", subfolder="scheduler", revision="onnx"
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", subfolder="scheduler", revision="onnx"
         )
         sd_pipe = OnnxStableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5",
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
             revision="onnx",
             scheduler=ddim_scheduler,
             safety_checker=None,
@@ -276,10 +276,10 @@ class OnnxStableDiffusionPipelineIntegrationTests(unittest.TestCase):
 
     def test_inference_k_lms(self):
         lms_scheduler = LMSDiscreteScheduler.from_pretrained(
-            "Jiali/stable-diffusion-1.5", subfolder="scheduler", revision="onnx"
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", subfolder="scheduler", revision="onnx"
         )
         sd_pipe = OnnxStableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5",
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
             revision="onnx",
             scheduler=lms_scheduler,
             safety_checker=None,
@@ -327,7 +327,7 @@ class OnnxStableDiffusionPipelineIntegrationTests(unittest.TestCase):
         test_callback_fn.has_been_called = False
 
         pipe = OnnxStableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5",
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
             revision="onnx",
             safety_checker=None,
             feature_extractor=None,
@@ -352,7 +352,7 @@ class OnnxStableDiffusionPipelineIntegrationTests(unittest.TestCase):
 
     def test_stable_diffusion_no_safety_checker(self):
         pipe = OnnxStableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5",
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
             revision="onnx",
             safety_checker=None,
             feature_extractor=None,

tests/pipelines/stable_diffusion/test_onnx_stable_diffusion_img2img.py

@@ -210,10 +210,10 @@ class OnnxStableDiffusionImg2ImgPipelineIntegrationTests(unittest.TestCase):
         )
         init_image = init_image.resize((768, 512))
         lms_scheduler = LMSDiscreteScheduler.from_pretrained(
-            "Jiali/stable-diffusion-1.5", subfolder="scheduler", revision="onnx"
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", subfolder="scheduler", revision="onnx"
         )
         pipe = OnnxStableDiffusionImg2ImgPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5",
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
             revision="onnx",
             scheduler=lms_scheduler,
             safety_checker=None,

tests/pipelines/stable_diffusion/test_stable_diffusion.py

@@ -1332,7 +1332,7 @@ class StableDiffusionPipelineCkptTests(unittest.TestCase):
 
     def test_download_from_hub(self):
         ckpt_paths = [
-            "https://huggingface.co/Jiali/stable-diffusion-1.5/blob/main/v1-5-pruned-emaonly.safetensors",
+            "https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-v1-5/blob/main/v1-5-pruned-emaonly.safetensors",
             "https://huggingface.co/WarriorMama777/OrangeMixs/blob/main/Models/AbyssOrangeMix/AbyssOrangeMix.safetensors",
         ]
 
@@ -1346,8 +1346,10 @@ class StableDiffusionPipelineCkptTests(unittest.TestCase):
         assert image_out.shape == (512, 512, 3)
 
     def test_download_local(self):
-        ckpt_filename = hf_hub_download("Jiali/stable-diffusion-1.5", filename="v1-5-pruned-emaonly.safetensors")
-        config_filename = hf_hub_download("Jiali/stable-diffusion-1.5", filename="v1-inference.yaml")
+        ckpt_filename = hf_hub_download(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", filename="v1-5-pruned-emaonly.safetensors"
+        )
+        config_filename = hf_hub_download("stable-diffusion-v1-5/stable-diffusion-v1-5", filename="v1-inference.yaml")
 
         pipe = StableDiffusionPipeline.from_single_file(
             ckpt_filename, config_files={"v1": config_filename}, torch_dtype=torch.float16
@@ -1402,7 +1404,9 @@ class StableDiffusionPipelineNightlyTests(unittest.TestCase):
         assert max_diff < 1e-3
 
     def test_stable_diffusion_1_5_pndm(self):
-        sd_pipe = StableDiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5").to(torch_device)
+        sd_pipe = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5").to(
+            torch_device
+        )
         sd_pipe.set_progress_bar_config(disable=None)
 
         inputs = self.get_inputs(torch_device)
@@ -1483,9 +1487,9 @@ class StableDiffusionPipelineDeviceMapTests(unittest.TestCase):
         return inputs
 
     def get_pipeline_output_without_device_map(self):
-        sd_pipe = StableDiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5", torch_dtype=torch.float16).to(
-            torch_device
-        )
+        sd_pipe = StableDiffusionPipeline.from_pretrained(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.float16
+        ).to(torch_device)
         sd_pipe.set_progress_bar_config(disable=True)
         inputs = self.get_inputs()
         no_device_map_image = sd_pipe(**inputs).images
@@ -1498,7 +1502,7 @@ class StableDiffusionPipelineDeviceMapTests(unittest.TestCase):
         no_device_map_image = self.get_pipeline_output_without_device_map()
 
         sd_pipe_with_device_map = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", device_map="balanced", torch_dtype=torch.float16
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", device_map="balanced", torch_dtype=torch.float16
         )
         sd_pipe_with_device_map.set_progress_bar_config(disable=True)
         inputs = self.get_inputs()
@@ -1509,7 +1513,7 @@ class StableDiffusionPipelineDeviceMapTests(unittest.TestCase):
 
     def test_components_put_in_right_devices(self):
         sd_pipe_with_device_map = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", device_map="balanced", torch_dtype=torch.float16
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", device_map="balanced", torch_dtype=torch.float16
         )
 
         assert len(set(sd_pipe_with_device_map.hf_device_map.values())) >= 2
@@ -1518,7 +1522,7 @@ class StableDiffusionPipelineDeviceMapTests(unittest.TestCase):
         no_device_map_image = self.get_pipeline_output_without_device_map()
 
         sd_pipe_with_device_map = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5",
+            "stable-diffusion-v1-5/stable-diffusion-v1-5",
             device_map="balanced",
             max_memory={0: "1GB", 1: "1GB"},
             torch_dtype=torch.float16,
@@ -1532,7 +1536,7 @@ class StableDiffusionPipelineDeviceMapTests(unittest.TestCase):
 
     def test_reset_device_map(self):
         sd_pipe_with_device_map = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", device_map="balanced", torch_dtype=torch.float16
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", device_map="balanced", torch_dtype=torch.float16
         )
         sd_pipe_with_device_map.reset_device_map()
 
@@ -1544,7 +1548,7 @@ class StableDiffusionPipelineDeviceMapTests(unittest.TestCase):
 
     def test_reset_device_map_to(self):
         sd_pipe_with_device_map = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", device_map="balanced", torch_dtype=torch.float16
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", device_map="balanced", torch_dtype=torch.float16
         )
         sd_pipe_with_device_map.reset_device_map()
 
@@ -1556,7 +1560,7 @@ class StableDiffusionPipelineDeviceMapTests(unittest.TestCase):
 
     def test_reset_device_map_enable_model_cpu_offload(self):
         sd_pipe_with_device_map = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", device_map="balanced", torch_dtype=torch.float16
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", device_map="balanced", torch_dtype=torch.float16
         )
         sd_pipe_with_device_map.reset_device_map()
 
@@ -1568,7 +1572,7 @@ class StableDiffusionPipelineDeviceMapTests(unittest.TestCase):
 
     def test_reset_device_map_enable_sequential_cpu_offload(self):
         sd_pipe_with_device_map = StableDiffusionPipeline.from_pretrained(
-            "Jiali/stable-diffusion-1.5", device_map="balanced", torch_dtype=torch.float16
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", device_map="balanced", torch_dtype=torch.float16
         )
         sd_pipe_with_device_map.reset_device_map()
 

tests/pipelines/stable_diffusion/test_stable_diffusion_img2img.py

@@ -566,7 +566,7 @@ class StableDiffusionImg2ImgPipelineSlowTests(unittest.TestCase):
             assert module.device == torch.device("cpu")
 
     def test_img2img_2nd_order(self):
-        sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("Jiali/stable-diffusion-1.5")
+        sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
         sd_pipe.scheduler = HeunDiscreteScheduler.from_config(sd_pipe.scheduler.config)
         sd_pipe.to(torch_device)
         sd_pipe.set_progress_bar_config(disable=None)
@@ -630,7 +630,7 @@ class StableDiffusionImg2ImgPipelineSlowTests(unittest.TestCase):
         assert np.abs(image_slice.flatten() - expected_slice).max() < 5e-3
 
     def test_img2img_safety_checker_works(self):
-        sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("Jiali/stable-diffusion-1.5")
+        sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
         sd_pipe.to(torch_device)
         sd_pipe.set_progress_bar_config(disable=None)
 
@@ -686,7 +686,7 @@ class StableDiffusionImg2ImgPipelineNightlyTests(unittest.TestCase):
         return inputs
 
     def test_img2img_pndm(self):
-        sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("Jiali/stable-diffusion-1.5")
+        sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
         sd_pipe.to(torch_device)
         sd_pipe.set_progress_bar_config(disable=None)
 
@@ -701,7 +701,7 @@ class StableDiffusionImg2ImgPipelineNightlyTests(unittest.TestCase):
         assert max_diff < 1e-3
 
     def test_img2img_ddim(self):
-        sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("Jiali/stable-diffusion-1.5")
+        sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
         sd_pipe.scheduler = DDIMScheduler.from_config(sd_pipe.scheduler.config)
         sd_pipe.to(torch_device)
         sd_pipe.set_progress_bar_config(disable=None)
@@ -717,7 +717,7 @@ class StableDiffusionImg2ImgPipelineNightlyTests(unittest.TestCase):
         assert max_diff < 1e-3
 
     def test_img2img_lms(self):
-        sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("Jiali/stable-diffusion-1.5")
+        sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
         sd_pipe.scheduler = LMSDiscreteScheduler.from_config(sd_pipe.scheduler.config)
         sd_pipe.to(torch_device)
         sd_pipe.set_progress_bar_config(disable=None)
@@ -733,7 +733,7 @@ class StableDiffusionImg2ImgPipelineNightlyTests(unittest.TestCase):
         assert max_diff < 1e-3
 
     def test_img2img_dpm(self):
-        sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("Jiali/stable-diffusion-1.5")
+        sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
         sd_pipe.scheduler = DPMSolverMultistepScheduler.from_config(sd_pipe.scheduler.config)
         sd_pipe.to(torch_device)
         sd_pipe.set_progress_bar_config(disable=None)

tests/pipelines/stable_diffusion/test_stable_diffusion_inpaint.py

@@ -767,7 +767,9 @@ class StableDiffusionInpaintPipelineSlowTests(unittest.TestCase):
         assert np.abs(expected_slice - image_slice).max() < 1e-3
 
     def test_stable_diffusion_simple_inpaint_ddim(self):
-        pipe = StableDiffusionInpaintPipeline.from_pretrained("Jiali/stable-diffusion-1.5", safety_checker=None)
+        pipe = StableDiffusionInpaintPipeline.from_pretrained(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None
+        )
         pipe.unet.set_default_attn_processor()
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
@@ -973,7 +975,9 @@ class StableDiffusionInpaintPipelineAsymmetricAutoencoderKLSlowTests(unittest.Te
 
     def test_stable_diffusion_simple_inpaint_ddim(self):
         vae = AsymmetricAutoencoderKL.from_pretrained("cross-attention/asymmetric-autoencoder-kl-x-1-5")
-        pipe = StableDiffusionInpaintPipeline.from_pretrained("Jiali/stable-diffusion-1.5", safety_checker=None)
+        pipe = StableDiffusionInpaintPipeline.from_pretrained(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None
+        )
         pipe.vae = vae
         pipe.unet.set_default_attn_processor()
         pipe.to(torch_device)

tests/pipelines/stable_diffusion_adapter/test_stable_diffusion_adapter.py

@@ -609,7 +609,7 @@ class StableDiffusionAdapterPipelineSlowTests(unittest.TestCase):
 
     def test_stable_diffusion_adapter_depth_sd_v15(self):
         adapter_model = "TencentARC/t2iadapter_depth_sd15v2"
-        sd_model = "Jiali/stable-diffusion-1.5"
+        sd_model = "stable-diffusion-v1-5/stable-diffusion-v1-5"
         prompt = "desk"
         image_url = "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/t2i_adapter/desk_depth.png"
         input_channels = 3
@@ -636,7 +636,7 @@ class StableDiffusionAdapterPipelineSlowTests(unittest.TestCase):
 
     def test_stable_diffusion_adapter_zoedepth_sd_v15(self):
         adapter_model = "TencentARC/t2iadapter_zoedepth_sd15v1"
-        sd_model = "Jiali/stable-diffusion-1.5"
+        sd_model = "stable-diffusion-v1-5/stable-diffusion-v1-5"
         prompt = "motorcycle"
         image_url = "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/t2i_adapter/motorcycle.png"
         input_channels = 3
@@ -660,7 +660,7 @@ class StableDiffusionAdapterPipelineSlowTests(unittest.TestCase):
 
     def test_stable_diffusion_adapter_canny_sd_v15(self):
         adapter_model = "TencentARC/t2iadapter_canny_sd15v2"
-        sd_model = "Jiali/stable-diffusion-1.5"
+        sd_model = "stable-diffusion-v1-5/stable-diffusion-v1-5"
         prompt = "toy"
         image_url = "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/t2i_adapter/toy_canny.png"
         input_channels = 1
@@ -688,7 +688,7 @@ class StableDiffusionAdapterPipelineSlowTests(unittest.TestCase):
 
     def test_stable_diffusion_adapter_sketch_sd15(self):
         adapter_model = "TencentARC/t2iadapter_sketch_sd15v2"
-        sd_model = "Jiali/stable-diffusion-1.5"
+        sd_model = "stable-diffusion-v1-5/stable-diffusion-v1-5"
         prompt = "cat"
         image_url = (
             "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/t2i_adapter/edge.png"

tests/pipelines/stable_diffusion_safe/test_safe_diffusion.py

@@ -277,7 +277,9 @@ class SafeDiffusionPipelineIntegrationTests(unittest.TestCase):
         torch.cuda.empty_cache()
 
     def test_harm_safe_stable_diffusion(self):
-        sd_pipe = StableDiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5", safety_checker=None)
+        sd_pipe = StableDiffusionPipeline.from_pretrained(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None
+        )
         sd_pipe.scheduler = LMSDiscreteScheduler.from_config(sd_pipe.scheduler.config)
         sd_pipe = sd_pipe.to(torch_device)
         sd_pipe.set_progress_bar_config(disable=None)
@@ -338,7 +340,9 @@ class SafeDiffusionPipelineIntegrationTests(unittest.TestCase):
         assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
 
     def test_nudity_safe_stable_diffusion(self):
-        sd_pipe = StableDiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5", safety_checker=None)
+        sd_pipe = StableDiffusionPipeline.from_pretrained(
+            "stable-diffusion-v1-5/stable-diffusion-v1-5", safety_checker=None
+        )
         sd_pipe.scheduler = LMSDiscreteScheduler.from_config(sd_pipe.scheduler.config)
         sd_pipe = sd_pipe.to(torch_device)
         sd_pipe.set_progress_bar_config(disable=None)
@@ -392,7 +396,7 @@ class SafeDiffusionPipelineIntegrationTests(unittest.TestCase):
         assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
 
     def test_nudity_safetychecker_safe_stable_diffusion(self):
-        sd_pipe = StableDiffusionPipeline.from_pretrained("Jiali/stable-diffusion-1.5")
+        sd_pipe = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
         sd_pipe = sd_pipe.to(torch_device)
         sd_pipe.set_progress_bar_config(disable=None)
 

tests/pipelines/test_pipelines_auto.py

@@ -40,7 +40,7 @@ from diffusers.utils.testing_utils import slow
 
 PRETRAINED_MODEL_REPO_MAPPING = OrderedDict(
     [
-        ("stable-diffusion", "Jiali/stable-diffusion-1.5"),
+        ("stable-diffusion", "stable-diffusion-v1-5/stable-diffusion-v1-5"),
         ("if", "DeepFloyd/IF-I-XL-v1.0"),
         ("kandinsky", "kandinsky-community/kandinsky-2-1"),
         ("kandinsky22", "kandinsky-community/kandinsky-2-2-decoder"),
@@ -539,7 +539,7 @@ class AutoPipelineIntegrationTest(unittest.TestCase):
 
     def test_controlnet(self):
         # test from_pretrained
-        model_repo = "Jiali/stable-diffusion-1.5"
+        model_repo = "stable-diffusion-v1-5/stable-diffusion-v1-5"
         controlnet_repo = "lllyasviel/sd-controlnet-canny"
 
         controlnet = ControlNetModel.from_pretrained(controlnet_repo, torch_dtype=torch.float16)

tests/pipelines/text_to_video_synthesis/test_text_to_video_zero.py

@@ -40,7 +40,7 @@ class TextToVideoZeroPipelineSlowTests(unittest.TestCase):
         torch.cuda.empty_cache()
 
     def test_full_model(self):
-        model_id = "Jiali/stable-diffusion-1.5"
+        model_id = "stable-diffusion-v1-5/stable-diffusion-v1-5"
         pipe = TextToVideoZeroPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to("cuda")
         pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
         generator = torch.Generator(device="cuda").manual_seed(0)