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Update Animatediff docs #6341

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Update Animatediff docs #6341

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87 changes: 73 additions & 14 deletions docs/source/en/api/pipelines/animatediff.md
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Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@ The following example demonstrates how to use a *MotionAdapter* checkpoint with

```python
import torch
from diffusers import MotionAdapter, AnimateDiffPipeline, DDIMScheduler
from diffusers import AnimateDiffPipeline, DDIMScheduler, MotionAdapter
from diffusers.utils import export_to_gif

# Load the motion adapter
Expand All @@ -47,7 +47,49 @@ adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-
model_id = "SG161222/Realistic_Vision_V5.1_noVAE"
pipe = AnimateDiffPipeline.from_pretrained(model_id, motion_adapter=adapter)
scheduler = DDIMScheduler.from_pretrained(
model_id, subfolder="scheduler", clip_sample=False, timestep_spacing="linspace", steps_offset=1
model_id,
subfolder="scheduler",
clip_sample=False,
timestep_spacing="linspace",
import torch
from diffusers import AnimateDiffPipeline, DDIMScheduler, MotionAdapter
from diffusers.utils import export_to_gif
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# Load the motion adapter
adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-2", torch_dtype=torch.float16)
# load SD 1.5 based finetuned model
model_id = "SG161222/Realistic_Vision_V5.1_noVAE"
pipe = AnimateDiffPipeline.from_pretrained(model_id, motion_adapter=adapter, torch_dtype=torch.float16)
scheduler = DDIMScheduler.from_pretrained(
model_id,
subfolder="scheduler",
clip_sample=False,
timestep_spacing="linspace",
beta_schedule="linear",
steps_offset=1,
)
pipe.scheduler = scheduler

# enable memory savings
pipe.enable_vae_slicing()
pipe.enable_model_cpu_offload()

output = pipe(
prompt=(
"masterpiece, bestquality, highlydetailed, ultradetailed, sunset, "
"orange sky, warm lighting, fishing boats, ocean waves seagulls, "
"rippling water, wharf, silhouette, serene atmosphere, dusk, evening glow, "
"golden hour, coastal landscape, seaside scenery"
),
negative_prompt="bad quality, worse quality",
num_frames=16,
guidance_scale=7.5,
num_inference_steps=25,
generator=torch.Generator("cpu").manual_seed(42),
)
frames = output.frames[0]
export_to_gif(frames, "animation.gif")
steps_offset=1,
)
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pipe.scheduler = scheduler

Expand Down Expand Up @@ -88,7 +130,7 @@ Here are some sample outputs:

<Tip>

AnimateDiff tends to work better with finetuned Stable Diffusion models. If you plan on using a scheduler that can clip samples, make sure to disable it by setting `clip_sample=False` in the scheduler as this can also have an adverse effect on generated samples.
AnimateDiff tends to work better with finetuned Stable Diffusion models. If you plan on using a scheduler that can clip samples, make sure to disable it by setting `clip_sample=False` in the scheduler as this can also have an adverse effect on generated samples. Additionally, the AnimateDiff checkpoints can be sensitive to the scheduler beta scheduler. We recommend setting this to `linear`.

</Tip>

Expand All @@ -98,18 +140,25 @@ Motion LoRAs are a collection of LoRAs that work with the `guoyww/animatediff-mo

```python
import torch
from diffusers import MotionAdapter, AnimateDiffPipeline, DDIMScheduler
from diffusers import AnimateDiffPipeline, DDIMScheduler, MotionAdapter
from diffusers.utils import export_to_gif

# Load the motion adapter
adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-2")
adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-2", torch_dtype=torch.float16)
# load SD 1.5 based finetuned model
model_id = "SG161222/Realistic_Vision_V5.1_noVAE"
pipe = AnimateDiffPipeline.from_pretrained(model_id, motion_adapter=adapter)
pipe.load_lora_weights("guoyww/animatediff-motion-lora-zoom-out", adapter_name="zoom-out")
pipe = AnimateDiffPipeline.from_pretrained(model_id, motion_adapter=adapter, torch_dtype=torch.float16)
pipe.load_lora_weights(
"guoyww/animatediff-motion-lora-zoom-out", adapter_name="zoom-out", torch_dtype=torch.float16
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)

scheduler = DDIMScheduler.from_pretrained(
model_id, subfolder="scheduler", clip_sample=False, timestep_spacing="linspace", steps_offset=1
model_id,
subfolder="scheduler",
clip_sample=False,
beta_schedule="linear",
timestep_spacing="linspace",
steps_offset=1,
)
pipe.scheduler = scheduler

Expand All @@ -132,6 +181,7 @@ output = pipe(
)
frames = output.frames[0]
export_to_gif(frames, "animation.gif")

```

<table>
Expand Down Expand Up @@ -160,21 +210,29 @@ Then you can use the following code to combine Motion LoRAs.

```python
import torch
from diffusers import MotionAdapter, AnimateDiffPipeline, DDIMScheduler
from diffusers import AnimateDiffPipeline, DDIMScheduler, MotionAdapter
from diffusers.utils import export_to_gif

# Load the motion adapter
adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-2")
adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-2", torch_dtype=torch.float16)
# load SD 1.5 based finetuned model
model_id = "SG161222/Realistic_Vision_V5.1_noVAE"
pipe = AnimateDiffPipeline.from_pretrained(model_id, motion_adapter=adapter)
pipe = AnimateDiffPipeline.from_pretrained(model_id, motion_adapter=adapter, torch_dtype=torch.float16)

pipe.load_lora_weights("diffusers/animatediff-motion-lora-zoom-out", adapter_name="zoom-out")
pipe.load_lora_weights("diffusers/animatediff-motion-lora-pan-left", adapter_name="pan-left")
pipe.load_lora_weights(
"diffusers/animatediff-motion-lora-zoom-out", adapter_name="zoom-out", torch_dtype=torch.float16
)
pipe.load_lora_weights(
"diffusers/animatediff-motion-lora-pan-left", adapter_name="pan-left", torch_dtype=torch.float16
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)
pipe.set_adapters(["zoom-out", "pan-left"], adapter_weights=[1.0, 1.0])

scheduler = DDIMScheduler.from_pretrained(
model_id, subfolder="scheduler", clip_sample=False, timestep_spacing="linspace", steps_offset=1
model_id,
subfolder="scheduler",
clip_sample=False,
timestep_spacing="linspace",
steps_offset=1,
)
pipe.scheduler = scheduler

Expand All @@ -197,6 +255,7 @@ output = pipe(
)
frames = output.frames[0]
export_to_gif(frames, "animation.gif")

```

<table>
Expand Down
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