Wan T2V 720p LoRA

Turbo-charged inference for Wan 2.1 14B. Unleashing high-res 720p text-to-video prowess with cutting-edge suite of video foundation models, LoRA effect added

Features

wan-2.1/t2v-720p-lora is an open-source AI video generation model developed by Alibaba Cloud, designed for text-to-video tasks. It incorporates Low-Rank Adaptation (LoRA) techniques, enabling efficient fine-tuning of pre-trained models to generate videos with specified effects from reference images. The 14-billion-parameter professional version excels in generating complex motions and simulating physical dynamics, delivering exceptional performance.

Built upon a causal 3D Variational Autoencoder (VAE) and Video Diffusion Transformer architecture, wan-2.1/t2v-720p-lora efficiently models spatiotemporal dependencies. In the authoritative VBench evaluation, the 14B version achieved a leading score of 86.22%, surpassing models like Sora, Luma, and Pika, and securing the top position. The model is available on Wavespeed AI, providing convenient access for developers.

Key Features

• LoRA-Enhanced Stylization: Incorporates LoRA modules to refine motion dynamics, preserve character consistency, and apply specific artistic styles without extensive retraining.
• High-Resolution Video Output: Capable of generating sharp 720p videos from text prompts, ensuring superior visual quality and motion diversity.
• State-of-the-Art Performance: Maintains top-tier performance, consistently outperforming existing open-source and commercial solutions across multiple benchmarks.
• Consumer-Grade GPU Compatibility: Optimized to run efficiently on widely available hardware, enabling broad accessibility for developers and creators.
• Accelerated Inference: Utilizes advanced acceleration techniques to reduce latency and computational overhead, enabling faster video generation without compromising quality.
• Multilingual Text Generation: Supports the generation of videos containing text in both Chinese and English, enhancing its adaptability for global applications.
• Powerful Video VAE: Integrates a robust variational autoencoder capable of encoding and decoding 1080p videos while preserving temporal information, making it an ideal foundation for video generation.

ComfyUI

wan-2.1/t2v-720p-lora is also available on ComfyUI, providing local inference capabilities through a node-based workflow, ensuring flexible and efficient image generation on your system.

Limitations

• Creative Focus: Designed for creative video synthesis from text; not intended for generating factually accurate or reliable content.
• Inherent Biases: As with any data-driven model, outputs may reflect biases present in the training data.
• Input Sensitivity: The quality and consistency of generated videos depend significantly on the quality of the input text prompt; subtle variations may lead to output variability.
• Task Scope: This model is exclusively built for text-to-video conversion at high resolution and does not support additional video generation tasks such as image-to-video or video editing.

Out-of-Scope Use

The model and its derivatives may not be used in any way that violates applicable national, federal, state, local, or international law or regulation, including but not limited to:

• Exploiting, harming, or attempting to exploit or harm minors, including solicitation, creation, acquisition, or dissemination of child exploitative content.
• Generating or disseminating verifiably false information with the intent to harm others.
• Creating or distributing personal identifiable information that could be used to harm an individual.
• Harassing, abusing, threatening, stalking, or bullying individuals or groups.
• Producing non-consensual nudity or illegal pornographic content.
• Making fully automated decisions that adversely affect an individual’s legal rights or create binding obligations.
• Facilitating large-scale disinformation campaigns.

Accelerated Inference

Our accelerated inference approach leverages advanced optimization technology from WavespeedAI. This innovative fusion technique significantly reduces computational overhead and latency, enabling rapid image generation without compromising quality. The entire system is designed to efficiently handle large-scale inference tasks while ensuring that real-time applications achieve an optimal balance between speed and accuracy. For further details, please refer to the blog post.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/t2v-720p-lora" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "prompt": "p1x4r_5ty13 Pixar animation style. A young girl with long flowing hair, wearing a shiny spacesuit, stands on a small moon and faces the camera with wide-eyed wonder. Behind her, a massive planet looms in the sky, casting a soft glow. Beside her, a tiny rover quietly beeps as it scans a glowing alien rock. Soft cinematic lighting, emotional and dreamy atmosphere, ultra-detailed and whimsical",
    "negative_prompt": "",
    "loras": [
        {
            "path": "Remade-AI/Fire",
            "scale": 1
        }
    ],
    "size": "1280*720",
    "num_inference_steps": 30,
    "duration": 5,
    "guidance_scale": 5,
    "flow_shift": 5,
    "seed": -1,
    "enable_safety_checker": true
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"

Parameters

Task Submission Parameters

Request Parameters

Response Parameters

Result Query Parameters

Result Request Parameters

Result Response Parameters