ShreejithSG
7833575da8
- Clean up basic_glm_image.py to match other example scripts (remove unnecessary comments, follow LTX2 pattern) - Fix attention_mask handling in LocalAttention to use set_forward_context properly instead of creating SDPAMetadata inline - SDPAMetadata import remains at top of file (no local import)
57 lines
1.3 KiB
Python
57 lines
1.3 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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"""
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GLM-Image inference example using FastVideo.
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This example demonstrates how to generate images using the GLM-Image model
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through FastVideo's VideoGenerator API.
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Usage:
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python examples/inference/basic/basic_glm_image.py
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"""
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import os
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from PIL import Image
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from fastvideo import VideoGenerator
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OUTPUT_PATH = "image_output"
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PROMPT = (
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"A beautiful landscape photography with rolling hills, "
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"a winding river, and a vibrant sunset in the background. "
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"Warm golden light, photorealistic style."
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)
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def main() -> None:
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generator = VideoGenerator.from_pretrained(
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"zai-org/GLM-Image",
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num_gpus=1,
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trust_remote_code=True,
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)
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os.makedirs(OUTPUT_PATH, exist_ok=True)
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result = generator.generate_video(
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prompt=PROMPT,
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output_path=OUTPUT_PATH,
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save_video=False,
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return_frames=True,
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height=1024,
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width=1024,
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num_inference_steps=50,
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guidance_scale=7.5,
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)
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if result and len(result) > 0:
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img = Image.fromarray(result[0])
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img.save(os.path.join(OUTPUT_PATH, "landscape.png"))
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print(f"Saved image to {OUTPUT_PATH}/landscape.png")
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generator.shutdown()
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if __name__ == "__main__":
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main()
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