Downloads · 30 days
0
jiachenli-ucsb/T2V-Turbo-VC2-Merged
T2V-Turbo-VC2-Merged is a machine learning model from jiachenli-ucsb. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
<table class="center" <td <video poster="" autoplay controls muted loop height="150%" playbackRate=2.0<source src="https://rg-lcd.s3.amazonaws.com/t2v-turbo-demo/t2v-turbo-vc2/4steps/0273.mp4" type="video/mp4"</video…
Downloads · 30 days
0
Access
Public
Updated Jun 3, 2024
Repo size
7.4 GB
Likes
2
Public
Click a slice to open those files.
.pt7.4 GB · 100%
From the Hugging Face model README
This repository contains unet_lora.pt that can turn VideoCrafter2 into our <span style="font-family: 'Courier New', monospace; font-weight: bold">T2V-Turbo</span> (VC2). Our <span style="font-family: 'Courier New', monospace; font-weight: bold">T2V-Turbo</span> (VC2) can achieve both fast and high-quality T2V generation. On VBench, the 4-step generation from our <span style="font-family: 'Courier New', monospace; font-weight: bold">T2V-Turbo</span> (VC2) even outperform proprietary systems, including Gen-2 and Pika. Please refer to our GitHub repo for detailed instructions.
This checkpoint is obtained by merging the UNet LoRA weight to the UNet of VideoCrafter2. Therefore, the checkpoint here is also under the apache-2.0 license.
You need to first clone our GitHub repo. Here are the codes to load the checkpoint.
from utils.common_utils import load_model_checkpoint
from utils.utils import instantiate_from_config
config = OmegaConf.load("configs/inference_t2v_512_v2.0.yaml")
model_config = config.pop("model", OmegaConf.create())
pretrained_t2v = instantiate_from_config(model_config)
unet_config = model_config["params"]["unet_config"]
unet_config["params"]["time_cond_proj_dim"] = 256
unet = instantiate_from_config(unet_config)
pretrained_t2v.model.diffusion_model = unet
pretrained_t2v = load_model_checkpoint(pretrained_t2v, "checkpoints/t2v_turbo_vc2.pt")
Our model is meant for research purposes.