Update

README.md

@@ -7,6 +7,7 @@ sdk: docker
 pinned: false
 license: mit
 duplicated_from: Tune-A-Video-library/Tune-A-Video-Training-UI
+suggested_hardware: t4-small
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -5,6 +5,7 @@ from __future__ import annotations
 import os
 
 import gradio as gr
+import torch
 
 from inference import InferencePipeline
 
@@ -23,13 +24,16 @@ class InferenceUtil:
         return base_model, training_prompt
 
 
-TITLE = '# [Tune-A-Video](https://tuneavideo.github.io/)'
+DESCRIPTION = '# [Tune-A-Video](https://tuneavideo.github.io/)'
+if not torch.cuda.is_available():
+    DESCRIPTION += '\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>'
+
 HF_TOKEN = os.getenv('HF_TOKEN')
 pipe = InferencePipeline(HF_TOKEN)
 app = InferenceUtil(HF_TOKEN)
 
 with gr.Blocks(css='style.css') as demo:
-    gr.Markdown(TITLE)
+    gr.Markdown(DESCRIPTION)
 
     with gr.Row():
         with gr.Column():
@@ -194,7 +198,7 @@ with gr.Blocks(css='style.css') as demo:
                     ],
                     outputs=result,
                     fn=pipe.run,
-                    cache_examples=os.getenv('SYSTEM') == 'spaces')
+                    cache_examples=os.getenv('CACHE_EXAMPLES') == '1')
 
     model_id.change(fn=app.load_model_info,
                     inputs=model_id,

requirements.txt

@@ -1,19 +1,19 @@
-accelerate==0.15.0
-bitsandbytes==0.35.4
+accelerate==0.20.3
+bitsandbytes==0.39.0
 decord==0.6.0
 diffusers[torch]==0.11.1
-einops==0.6.0
+einops==0.6.1
 ftfy==6.1.1
-gradio==3.18.0
-huggingface-hub==0.12.0
-imageio==2.25.0
+gradio==3.34.0
+huggingface-hub==0.15.1
+imageio==2.31.0
 imageio-ffmpeg==0.4.8
 omegaconf==2.3.0
-Pillow==9.4.0
-python-slugify==7.0.0
-tensorboard==2.11.2
+Pillow==9.5.0
+python-slugify==8.0.1
+tensorboard==2.12.3
 torch==1.13.1
 torchvision==0.14.1
-transformers==4.26.0
-triton==2.0.0.dev20221202
+transformers==4.30.2
+triton==2.0.0
 xformers==0.0.16