m_inference_steps = 25  # Number of denoising steps
>>> guidance_scale = 7.5  # Scale for classifier-free guidance
>>> generator = torch.manual_seed(0)  # Seed generator to create the inital latent noise
>>> batch_size = len(prompt)
Tokenize the text and generate the embeddings from the prompt:


	Copied
>>> text_input = tokenizer(
...     prompt, padding="max_length", max_length=tokenizer.model_max_length, truncation=True, return_tensors="pt"
