Update README.md

README.md

@@ -1,58 +1,60 @@
----
-license: apache-2.0
-language:
-  - en
-tags:
- - video
- - genmo
- - diffusers
-pipeline_tag: text-to-video
-library_name: diffusers
----
-# 🎥 Distilled Mochi Transformer
-Current repository contains distilled transformer for genmoai mochi-1. 
-This transformer consists of 42 blocks vs 48 blocks in original transformer.
-
-### Training details
-We have analized MSE of latent after each block and iteratively dropped blocks which have minimum value of MSE.
-
-After each block drop we have trained neighboring blocks (one before and one after deleted block) for 1K steps.
-
-### 🚀 Try it here: [Interactive Demo](https://nim.video/create/2855fa68-21b1-4114-b366-53e5e4705ebf?workflow=image2video)
-
----
-
-
-## Usage
-#### Minimal code example
-```python
-import torch
-from diffusers import MochiPipeline, MochiTransformer3DModel
-from diffusers.utils import export_to_video
-
-transformer = MochiTransformer3DModel.from_pretrained(
-    "NimVideo/mochi-1-transformer-42",
-    torch_dtype=torch.bfloat16,
-)
-pipe = MochiPipeline.from_pretrained(
-    "genmo/mochi-1-preview", 
-    transformer=transformer,
-    variant="bf16", 
-    torch_dtype=torch.bfloat16
-)
-
-pipe.enable_model_cpu_offload()
-pipe.enable_vae_tiling()
-
-prompt = "Close-up of a chameleon's eye, with its scaly skin changing color. Ultra high resolution 4k."
-frames = pipe(prompt, num_frames=85).frames[0]
-
-export_to_video(frames, "mochi.mp4", fps=30)
-```
-
-
-## Acknowledgements
-Original code and models [mochi](https://github.com/genmoai/mochi).  
-
-## Contacts
-<p>Issues should be raised directly in the repository.</p>
+---
+license: apache-2.0
+language:
+  - en
+tags:
+ - video
+ - genmo
+ - diffusers
+pipeline_tag: text-to-video
+library_name: diffusers
+---
+# 🎥 Distilled Mochi Transformer
+Current repository contains distilled transformer for genmoai mochi-1. 
+This transformer consists of 42 blocks vs 48 blocks in original transformer.
+
+### Training details
+We have analized MSE of latent after each block and iteratively dropped blocks which have minimum value of MSE.
+
+<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/63fde49f6315a264aba6a7ed/ILt2OOC_La0hcQIedkNhx.mp4"></video>
+
+After each block drop we have trained neighboring blocks (one before and one after deleted block) for 1K steps.
+
+### 🚀 Try it here: [Interactive Demo](https://nim.video/create/2855fa68-21b1-4114-b366-53e5e4705ebf?workflow=image2video)
+
+---
+
+
+## Usage
+#### Minimal code example
+```python
+import torch
+from diffusers import MochiPipeline, MochiTransformer3DModel
+from diffusers.utils import export_to_video
+
+transformer = MochiTransformer3DModel.from_pretrained(
+    "NimVideo/mochi-1-transformer-42",
+    torch_dtype=torch.bfloat16,
+)
+pipe = MochiPipeline.from_pretrained(
+    "genmo/mochi-1-preview", 
+    transformer=transformer,
+    variant="bf16", 
+    torch_dtype=torch.bfloat16
+)
+
+pipe.enable_model_cpu_offload()
+pipe.enable_vae_tiling()
+
+prompt = "Close-up of a chameleon's eye, with its scaly skin changing color. Ultra high resolution 4k."
+frames = pipe(prompt, num_frames=85).frames[0]
+
+export_to_video(frames, "mochi.mp4", fps=30)
+```
+
+
+## Acknowledgements
+Original code and models [mochi](https://github.com/genmoai/mochi).  
+
+## Contacts
+<p>Issues should be raised directly in the repository.</p>