Text-to-Video
Diffusers
Safetensors
PyTorch
Transformers
English
TextToVideoSDPipeline
video-generation
generative-ai
diffusion
Instructions to use Deepak1206/text-to-video-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Deepak1206/text-to-video-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Deepak1206/text-to-video-model", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Transformers
How to use Deepak1206/text-to-video-model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Deepak1206/text-to-video-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<|startoftext|>", | |
| "do_lower_case": true, | |
| "eos_token": "<|endoftext|>", | |
| "errors": "replace", | |
| "is_local": true, | |
| "local_files_only": false, | |
| "model_max_length": 77, | |
| "pad_token": "!", | |
| "tokenizer_class": "CLIPTokenizer", | |
| "unk_token": "<|endoftext|>" | |
| } | |