text: Title: pipe.disable_model_cpu_offload
  Body: **Is your feature request related to a problem? Please describe.**
  
  If I enable the following in Gradio interface
  sana_pipe.enable_model_cpu_offload()
  
  and during next generation I want to disable cpu offload, how to do it? I mentioned Gradio specifically as command line inference will not have this problem unless after initializing pipe you generate multiple times with and without cpu offload.
  
  I already searched but nothing found
  https://github.com/search?q=repo%3Ahuggingface%2Fdiffusers%20disable_model_cpu_offload&type=code
  
  **Describe the solution you'd like.**
  Add method to disable for 
  1. enable_model_cpu_offload()
  2. enable_sequential_cpu_offload()
  
  **Describe alternatives you've considered.**
  I will have to delete the pipe completely and load again for each inference in Gradio UI
  
  Kindly suggest if any alternative solution.
  
  
  ```
  import torch
  from diffusers import SanaPipeline
  
  pipe = SanaPipeline.from_pretrained(
  	"Efficient-Large-Model/Sana_1600M_1024px_BF16_diffusers", torch_dtype=torch.float32
  )
  pipe.to("cuda")
  pipe.text_encoder.to(torch.bfloat16)
  pipe.transformer = pipe.transformer.to(torch.bfloat16)
  pipe.enable_model_cpu_offload()
  
  image = pipe(prompt='a cyberpunk cat with a neon sign that says "Sana"')[0]
  image[0].save("output.png")
  
  pipe.disable_model_cpu_offload()
  image = pipe(prompt='a cyberpunk cat with a neon sign that says "Sana 1"')[0]
  image[0].save("output1.png")
  ```
  
  P.S. How to delete a pipe completely so all models are removed completely and GPU memory is freed
  I did checked documentation but unable to find find anything relevant
  https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/sana/pipeline_sana.py
  
  https://github.com/huggingface/diffusers/blob/4e44534845d35248436abf87688906f52e71b868/src/diffusers/pipelines/pipeline_utils.py
  