test_pipe.py

import torch
from grn_pipeline import GRNPipeline

# 加载
pipe = GRNPipeline.from_pretrained(
    model_path='/tmp/weights/9a8a674133266e996d8d56e784a10d67.pth',
    vae_path='/tmp/weights/HBQ_tokenizer_64dim_M4.ckpt',
    text_encoder_ckpt='/tmp/weights/umt5-xxl',
    torch_dtype=torch.bfloat16
)

# 移动到设备
pipe = pipe.to('cuda')

# 生成图像
result = pipe(
    prompt="A cute cat playing in the garden",
    guidance_scale=3.0,
    num_inference_steps=50,
    width=1024,
    height=1024,
    content_type='image',
    seed=42
)
image = result.images[0]

import pdb; pdb.set_trace()

# # 生成视频
# result = pipe(
#     prompt="A dog chasing a butterfly",
#     content_type='video'
# )
# video = result.videos[0]