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amused update links to new repo #6344

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Dec 26, 2023
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amused update links to new repo #6344

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amused update links to new repo
williamberman Dec 26, 2023
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williamberman Dec 26, 2023
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4 changes: 2 additions & 2 deletions docs/source/en/api/pipelines/amused.md
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Expand Up @@ -18,8 +18,8 @@ Amused is a vqvae token based transformer that can generate an image in fewer fo

| Model | Params |
|-------|--------|
| [amused-256](https://huggingface.co/huggingface/amused-256) | 603M |
| [amused-512](https://huggingface.co/huggingface/amused-512) | 608M |
| [amused-256](https://huggingface.co/amused/amused-256) | 603M |
| [amused-512](https://huggingface.co/amused/amused-512) | 608M |

## AmusedPipeline

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16 changes: 8 additions & 8 deletions examples/amused/README.md
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Expand Up @@ -29,7 +29,7 @@ accelerate launch train_amused.py \
--train_batch_size <batch size> \
--gradient_accumulation_steps <gradient accumulation steps> \
--learning_rate 1e-4 \
--pretrained_model_name_or_path huggingface/amused-256 \
--pretrained_model_name_or_path amused/amused-256 \
--instance_data_dataset 'm1guelpf/nouns' \
--image_key image \
--prompt_key text \
Expand Down Expand Up @@ -70,7 +70,7 @@ accelerate launch train_amused.py \
--gradient_accumulation_steps <gradient accumulation steps> \
--learning_rate 2e-5 \
--use_8bit_adam \
--pretrained_model_name_or_path huggingface/amused-256 \
--pretrained_model_name_or_path amused/amused-256 \
--instance_data_dataset 'm1guelpf/nouns' \
--image_key image \
--prompt_key text \
Expand Down Expand Up @@ -109,7 +109,7 @@ accelerate launch train_amused.py \
--gradient_accumulation_steps <gradient accumulation steps> \
--learning_rate 8e-4 \
--use_lora \
--pretrained_model_name_or_path huggingface/amused-256 \
--pretrained_model_name_or_path amused/amused-256 \
--instance_data_dataset 'm1guelpf/nouns' \
--image_key image \
--prompt_key text \
Expand Down Expand Up @@ -155,7 +155,7 @@ accelerate launch train_amused.py \
--train_batch_size <batch size> \
--gradient_accumulation_steps <gradient accumulation steps> \
--learning_rate 8e-5 \
--pretrained_model_name_or_path huggingface/amused-512 \
--pretrained_model_name_or_path amused/amused-512 \
--instance_data_dataset 'monadical-labs/minecraft-preview' \
--prompt_prefix 'minecraft ' \
--image_key image \
Expand Down Expand Up @@ -191,7 +191,7 @@ accelerate launch train_amused.py \
--train_batch_size <batch size> \
--gradient_accumulation_steps <gradient accumulation steps> \
--learning_rate 5e-6 \
--pretrained_model_name_or_path huggingface/amused-512 \
--pretrained_model_name_or_path amused/amused-512 \
--instance_data_dataset 'monadical-labs/minecraft-preview' \
--prompt_prefix 'minecraft ' \
--image_key image \
Expand Down Expand Up @@ -228,7 +228,7 @@ accelerate launch train_amused.py \
--gradient_accumulation_steps <gradient accumulation steps> \
--learning_rate 1e-4 \
--use_lora \
--pretrained_model_name_or_path huggingface/amused-512 \
--pretrained_model_name_or_path amused/amused-512 \
--instance_data_dataset 'monadical-labs/minecraft-preview' \
--prompt_prefix 'minecraft ' \
--image_key image \
Expand Down Expand Up @@ -276,7 +276,7 @@ accelerate launch train_amused.py \
--mixed_precision fp16 \
--report_to wandb \
--use_lora \
--pretrained_model_name_or_path huggingface/amused-256 \
--pretrained_model_name_or_path amused/amused-256 \
--train_batch_size 1 \
--lr_scheduler constant \
--learning_rate 4e-4 \
Expand Down Expand Up @@ -308,7 +308,7 @@ accelerate launch train_amused.py \
--mixed_precision fp16 \
--report_to wandb \
--use_lora \
--pretrained_model_name_or_path huggingface/amused-512 \
--pretrained_model_name_or_path amused/amused-512 \
--train_batch_size 1 \
--lr_scheduler constant \
--learning_rate 1e-3 \
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2 changes: 1 addition & 1 deletion src/diffusers/pipelines/amused/pipeline_amused.py
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Expand Up @@ -31,7 +31,7 @@
>>> from diffusers import AmusedPipeline

>>> pipe = AmusedPipeline.from_pretrained(
... "huggingface/amused-512", variant="fp16", torch_dtype=torch.float16
... "amused/amused-512", variant="fp16", torch_dtype=torch.float16
... )
>>> pipe = pipe.to("cuda")

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2 changes: 1 addition & 1 deletion src/diffusers/pipelines/amused/pipeline_amused_img2img.py
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Expand Up @@ -32,7 +32,7 @@
>>> from diffusers.utils import load_image

>>> pipe = AmusedImg2ImgPipeline.from_pretrained(
... "huggingface/amused-512", variant="fp16", torch_dtype=torch.float16
... "amused/amused-512", variant="fp16", torch_dtype=torch.float16
... )
>>> pipe = pipe.to("cuda")

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2 changes: 1 addition & 1 deletion src/diffusers/pipelines/amused/pipeline_amused_inpaint.py
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Expand Up @@ -33,7 +33,7 @@
>>> from diffusers.utils import load_image

>>> pipe = AmusedInpaintPipeline.from_pretrained(
... "huggingface/amused-512", variant="fp16", torch_dtype=torch.float16
... "amused/amused-512", variant="fp16", torch_dtype=torch.float16
... )
>>> pipe = pipe.to("cuda")

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8 changes: 4 additions & 4 deletions tests/pipelines/amused/test_amused.py
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Expand Up @@ -133,7 +133,7 @@ def test_inference_batch_single_identical(self):
@require_torch_gpu
class AmusedPipelineSlowTests(unittest.TestCase):
def test_amused_256(self):
pipe = AmusedPipeline.from_pretrained("huggingface/amused-256")
pipe = AmusedPipeline.from_pretrained("amused/amused-256")
pipe.to(torch_device)

image = pipe("dog", generator=torch.Generator().manual_seed(0), num_inference_steps=2, output_type="np").images
Expand All @@ -145,7 +145,7 @@ def test_amused_256(self):
assert np.abs(image_slice - expected_slice).max() < 3e-3

def test_amused_256_fp16(self):
pipe = AmusedPipeline.from_pretrained("huggingface/amused-256", variant="fp16", torch_dtype=torch.float16)
pipe = AmusedPipeline.from_pretrained("amused/amused-256", variant="fp16", torch_dtype=torch.float16)
pipe.to(torch_device)

image = pipe("dog", generator=torch.Generator().manual_seed(0), num_inference_steps=2, output_type="np").images
Expand All @@ -157,7 +157,7 @@ def test_amused_256_fp16(self):
assert np.abs(image_slice - expected_slice).max() < 7e-3

def test_amused_512(self):
pipe = AmusedPipeline.from_pretrained("huggingface/amused-512")
pipe = AmusedPipeline.from_pretrained("amused/amused-512")
pipe.to(torch_device)

image = pipe("dog", generator=torch.Generator().manual_seed(0), num_inference_steps=2, output_type="np").images
Expand All @@ -169,7 +169,7 @@ def test_amused_512(self):
assert np.abs(image_slice - expected_slice).max() < 3e-3

def test_amused_512_fp16(self):
pipe = AmusedPipeline.from_pretrained("huggingface/amused-512", variant="fp16", torch_dtype=torch.float16)
pipe = AmusedPipeline.from_pretrained("amused/amused-512", variant="fp16", torch_dtype=torch.float16)
pipe.to(torch_device)

image = pipe("dog", generator=torch.Generator().manual_seed(0), num_inference_steps=2, output_type="np").images
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12 changes: 4 additions & 8 deletions tests/pipelines/amused/test_amused_img2img.py
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Expand Up @@ -137,7 +137,7 @@ def test_inference_batch_single_identical(self):
@require_torch_gpu
class AmusedImg2ImgPipelineSlowTests(unittest.TestCase):
def test_amused_256(self):
pipe = AmusedImg2ImgPipeline.from_pretrained("huggingface/amused-256")
pipe = AmusedImg2ImgPipeline.from_pretrained("amused/amused-256")
pipe.to(torch_device)

image = (
Expand All @@ -162,9 +162,7 @@ def test_amused_256(self):
assert np.abs(image_slice - expected_slice).max() < 1e-2

def test_amused_256_fp16(self):
pipe = AmusedImg2ImgPipeline.from_pretrained(
"huggingface/amused-256", torch_dtype=torch.float16, variant="fp16"
)
pipe = AmusedImg2ImgPipeline.from_pretrained("amused/amused-256", torch_dtype=torch.float16, variant="fp16")
pipe.to(torch_device)

image = (
Expand All @@ -189,7 +187,7 @@ def test_amused_256_fp16(self):
assert np.abs(image_slice - expected_slice).max() < 1e-2

def test_amused_512(self):
pipe = AmusedImg2ImgPipeline.from_pretrained("huggingface/amused-512")
pipe = AmusedImg2ImgPipeline.from_pretrained("amused/amused-512")
pipe.to(torch_device)

image = (
Expand All @@ -213,9 +211,7 @@ def test_amused_512(self):
assert np.abs(image_slice - expected_slice).max() < 0.1

def test_amused_512_fp16(self):
pipe = AmusedImg2ImgPipeline.from_pretrained(
"huggingface/amused-512", variant="fp16", torch_dtype=torch.float16
)
pipe = AmusedImg2ImgPipeline.from_pretrained("amused/amused-512", variant="fp16", torch_dtype=torch.float16)
pipe.to(torch_device)

image = (
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12 changes: 4 additions & 8 deletions tests/pipelines/amused/test_amused_inpaint.py
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Expand Up @@ -141,7 +141,7 @@ def test_inference_batch_single_identical(self):
@require_torch_gpu
class AmusedInpaintPipelineSlowTests(unittest.TestCase):
def test_amused_256(self):
pipe = AmusedInpaintPipeline.from_pretrained("huggingface/amused-256")
pipe = AmusedInpaintPipeline.from_pretrained("amused/amused-256")
pipe.to(torch_device)

image = (
Expand Down Expand Up @@ -174,9 +174,7 @@ def test_amused_256(self):
assert np.abs(image_slice - expected_slice).max() < 0.1

def test_amused_256_fp16(self):
pipe = AmusedInpaintPipeline.from_pretrained(
"huggingface/amused-256", variant="fp16", torch_dtype=torch.float16
)
pipe = AmusedInpaintPipeline.from_pretrained("amused/amused-256", variant="fp16", torch_dtype=torch.float16)
pipe.to(torch_device)

image = (
Expand Down Expand Up @@ -209,7 +207,7 @@ def test_amused_256_fp16(self):
assert np.abs(image_slice - expected_slice).max() < 0.1

def test_amused_512(self):
pipe = AmusedInpaintPipeline.from_pretrained("huggingface/amused-512")
pipe = AmusedInpaintPipeline.from_pretrained("amused/amused-512")
pipe.to(torch_device)

image = (
Expand Down Expand Up @@ -242,9 +240,7 @@ def test_amused_512(self):
assert np.abs(image_slice - expected_slice).max() < 0.05

def test_amused_512_fp16(self):
pipe = AmusedInpaintPipeline.from_pretrained(
"huggingface/amused-512", variant="fp16", torch_dtype=torch.float16
)
pipe = AmusedInpaintPipeline.from_pretrained("amused/amused-512", variant="fp16", torch_dtype=torch.float16)
pipe.to(torch_device)

image = (
Expand Down
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