| --- | |
| license: other | |
| ---pip install transformers torch torchvision | |
| from transformers import T5ForConditionalGeneration, T5Tokenizer | |
| import torch | |
| import torchvision.transforms as transforms | |
| from torchvision.io import write_video | |
| model = T5ForConditionalGeneration.from_pretrained("t5-base") | |
| tokenizer = T5Tokenizer.from_pretrained("t5-base") | |
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| model = model.to(device) | |
| def generate_video_from_text(text): | |
| input_ids = tokenizer.encode(text, return_tensors="pt").to(device) | |
| output = model.generate(input_ids) | |
| video_frames = output[0].cpu().numpy() | |
| # Convert frames to a video | |
| frames = [torch.tensor(frame, dtype=torch.uint8).permute(1, 2, 0) for frame in video_frames] | |
| video = torch.stack(frames) | |
| video = video.permute(0, 3, 1, 2) # (T, C, H, W) | |
| return video | |