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
File size: 549 Bytes
68fedc6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | {
"architectures": [
"CLIPTextModel"
],
"attention_dropout": 0.0,
"bos_token_id": 0,
"dropout": 0.0,
"dtype": "float16",
"eos_token_id": 2,
"hidden_act": "gelu",
"hidden_size": 1024,
"initializer_factor": 1.0,
"initializer_range": 0.02,
"intermediate_size": 4096,
"layer_norm_eps": 1e-05,
"max_position_embeddings": 77,
"model_type": "clip_text_model",
"num_attention_heads": 16,
"num_hidden_layers": 23,
"pad_token_id": 1,
"projection_dim": 512,
"transformers_version": "5.15.0",
"vocab_size": 49408
}
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