Create README.md

README.md

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+---
+pipeline_tag: text-to-video
+---
+AnimateDiff is a method that allows you to create videos using pre-existing Stable Diffusion Text to Image models.
+
+Converted https://huggingface.co/guoyww/animatediff/blob/main/v3_sd15_mm.ckpt to Huggingface Diffusers format 
+using Diffuser's convetion script (available https://github.com/huggingface/diffusers/blob/main/scripts/convert_animatediff_motion_module_to_diffusers.py)
+
+The following example demonstrates how you can utilize the motion modules with an existing Stable Diffusion text to image model.
+
+
+```python
+import torch
+from diffusers import MotionAdapter, AnimateDiffPipeline, DDIMScheduler
+from diffusers.utils import export_to_gif
+
+# Load the motion adapter
+adapter = MotionAdapter.from_pretrained("Warvito/animatediff-motion-adapter-v1-5-3")
+# load SD 1.5 based finetuned model
+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
+)
+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")
+```
+