update the req

README.md

@@ -271,7 +271,6 @@ pipe.vae.enable_tiling()
   increases by about 10%. Only the `diffusers` version of the model supports quantization.
 + The model only supports English input; other languages can be translated into English during refinement by a large
   model.
-+
 
 ## Friendly Links
 

inference/gradio_composite_demo/rife_model.py

@@ -42,10 +42,10 @@ def ssim_interpolation_rife(model, samples, exp=1, upscale_amount=1, output_devi
     output = []
     # [f, c, h, w]
     for b in range(samples.shape[0]):
-        frame = samples[b: b + 1]
+        frame = samples[b : b + 1]
         _, _, h, w = frame.shape
-        I0 = samples[b: b + 1]
-        I1 = samples[b + 1: b + 2] if b + 2 < samples.shape[0] else samples[-1:]
+        I0 = samples[b : b + 1]
+        I1 = samples[b + 1 : b + 2] if b + 2 < samples.shape[0] else samples[-1:]
         I0 = pad_image(I0, upscale_amount).to(torch.float)
         I1 = pad_image(I1, upscale_amount).to(torch.float)
         # [c, h, w]
@@ -66,11 +66,11 @@ def ssim_interpolation_rife(model, samples, exp=1, upscale_amount=1, output_devi
 
         tmp_output = []
         if ssim < 0.2:
-            for i in range((2 ** exp) - 1):
+            for i in range((2**exp) - 1):
                 tmp_output.append(I0)
 
         else:
-            tmp_output = make_inference(model, I0, I1, upscale_amount, 2 ** exp - 1) if exp else []
+            tmp_output = make_inference(model, I0, I1, upscale_amount, 2**exp - 1) if exp else []
 
         frame = pad_image(frame, upscale_amount)
         tmp_output = [frame] + tmp_output

requirements.txt

@@ -1,5 +1,5 @@
 diffusers>=0.30.1 #git+https://github.com/huggingface/diffusers.git@main#egg=diffusers is suggested
-transformers>=4.44.0  # The development team is working on version 0.44.2
+transformers>=4.44.2  # The development team is working on version 4.44.2
 accelerate>=0.33.0 #git+https://github.com/huggingface/accelerate.git@main#egg=accelerate is suggested
 sentencepiece>=0.2.0 # T5 used
 SwissArmyTransformer>=0.4.12
@@ -7,7 +7,7 @@ numpy==1.26.0
 torch>=2.4.0 # Tested in 2.2 2.3 2.4 and 2.5, The development team is working on version 2.4.0.
 torchvision>=0.19.0 # The development team is working on version 0.19.0.
 gradio>=4.42.0 # For HF gradio demo
-streamlit>=1.37.1 # For streamlit web demo
+streamlit>=1.38.0 # For streamlit web demo
 imageio==2.34.2 # For diffusers inference export video
 imageio-ffmpeg==0.5.1 # For diffusers inference export video
 openai>=1.42.0 # For prompt refiner