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import argparse |
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import os |
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import torch |
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from diffusers import AutoPipelineForText2Image |
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from huggingface_hub import HfApi, login |
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from slugify import slugify |
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def main(prompt: str, repo: str, hf_token: str = None): |
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HF_TOKEN = hf_token or os.environ.get("HF_TOKEN") |
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if HF_TOKEN: |
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login(token=HF_TOKEN) |
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name = slugify(prompt) |
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filename = f"{name}.png" |
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model_id = "stabilityai/stable-diffusion-xl-base-1.0" |
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api = HfApi() |
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print(f"Loading model: {model_id}...") |
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pipe = AutoPipelineForText2Image.from_pretrained( |
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model_id, torch_dtype=torch.float16, variant="fp16" |
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).to("cuda") |
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print(f"Generating image for prompt: '{prompt}'...") |
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image = pipe(prompt=prompt).images[0] |
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temp_image_path = f"/tmp/{filename}" |
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image.save(temp_image_path) |
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print(f"Image saved temporarily to {temp_image_path}") |
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print(f"Uploading {filename} to dataset repository: {repo}...") |
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api.upload_file( |
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path_or_fileobj=temp_image_path, |
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path_in_repo=filename, |
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repo_id=repo, |
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repo_type="dataset", |
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commit_message=f"add {filename}" |
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) |
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repo_url = f"https://huggingface.co/datasets/{repo}/tree/main" |
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print(f"View it here: {repo_url}") |
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if __name__ == "__main__": |
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parser = argparse.ArgumentParser(description="Generate a single image using HF Jobs.") |
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parser.add_argument("--prompt", required=True, help="The text prompt to generate an image from.") |
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parser.add_argument("--repo", required=True, help="Your destination dataset repository ID.") |
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parser.add_argument("--hf-token", help="Hugging Face API token.") |
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args = parser.parse_args() |
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main(prompt=args.prompt, repo=args.repo, hf_token=args.hf_token) |
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