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--- |
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base_model: |
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- Wan-AI/Wan2.2-I2V-A14B |
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license: apache-2.0 |
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pipeline_tag: image-to-video |
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--- |
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# FastVideo CausalWan2.2-I2V-A14B-Preview-Diffusers Model |
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<p align="center"> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6532f70333c5982a291ca909/zAB7U0da8_8fP1N0DgUS2.png" width="200"/> |
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</p> |
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<div> |
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<div align="center"> |
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<a href="https://github.com/hao-ai-lab/FastVideo" target="_blank">FastVideo Team</a>  |
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</div> |
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<div align="center"> |
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<a href="https://github.com/hao-ai-lab/FastVideo">Github</a> | |
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<a href="https://hao-ai-lab.github.io/FastVideo">Project Page</a> |
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</div> |
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</div> |
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## Disclaimer |
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Note that this is a preview model, meaning there are still quality issues. The inference speed is also unoptimized. |
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## Introduction |
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We're excited to introduce the **CausalWan2.2 I2V A14B series**—a new line of models. |
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--- |
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## Model Overview |
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- 8-step inference is supported. |
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- Try it out on **FastVideo** — we support a wide range of GPUs from **H100** to **4090**, and also support **Mac** users! |
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## Inference code |
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```python |
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from fastvideo import VideoGenerator, SamplingParam |
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import json |
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# from fastvideo.configs.sample import SamplingParam |
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OUTPUT_PATH = "video_samples_self_forcing_causal_wan2_2_14B_i2v" |
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def main(): |
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# FastVideo will automatically use the optimal default arguments for the |
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# model. |
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# If a local path is provided, FastVideo will make a best effort |
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# attempt to identify the optimal arguments. |
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generator = VideoGenerator.from_pretrained( |
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"FastVideo/SFWan2.2-I2V-A14B-Preview-Diffusers", |
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# FastVideo will automatically handle distributed setup |
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num_gpus=1, |
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use_fsdp_inference=True, |
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dit_cpu_offload=True, # DiT need to be offloaded for MoE |
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dit_precision="fp32", |
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vae_cpu_offload=False, |
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text_encoder_cpu_offload=True, |
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dmd_denoising_steps=[1000, 850, 700, 550, 350, 275, 200, 125], |
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# Set pin_cpu_memory to false if CPU RAM is limited and there're no frequent CPU-GPU transfer |
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pin_cpu_memory=True, |
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# image_encoder_cpu_offload=False, |
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) |
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sampling_param = SamplingParam.from_pretrained("FastVideo/SFWan2.2-I2V-A14B-Preview-Diffusers") |
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sampling_param.num_frames = 81 |
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sampling_param.width = 832 |
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sampling_param.height = 480 |
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sampling_param.seed = 1000 |
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with open("prompts/mixkit_i2v.jsonl", "r") as f: |
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prompt_image_pairs = json.load(f) |
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for prompt_image_pair in prompt_image_pairs: |
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prompt = prompt_image_pair["prompt"] |
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image_path = prompt_image_pair["image_path"] |
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_ = generator.generate_video(prompt, image_path=image_path, output_path=OUTPUT_PATH, save_video=True, sampling_param=sampling_param) |
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if __name__ == "__main__": |
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main() |
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``` |
