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import hf_image_uploader as hiu |
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from safetensors.torch import load_file |
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from huggingface_hub import snapshot_download |
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from diffusers import DiffusionPipeline |
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import torch |
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import json |
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import os |
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model_id = "multimodalart/sdxl-emoji" |
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folder = snapshot_download(model_id) |
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with open(os.path.join(folder, "special_params.json"), 'r') as json_file: |
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data = json.load(json_file) |
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token, token_2 = data["TOK"][:4], data["TOK"][4:] |
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state_dict = load_file(os.path.join(folder, "embeddings.pti")) |
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text_encoder_sd = state_dict["text_encoders_0"] |
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text_encoder_2_sd = state_dict["text_encoders_1"] |
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pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16) |
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pipe.load_textual_inversion(text_encoder_sd, token=token, text_encoder=pipe.text_encoder, tokenizer=pipe.tokenizer) |
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pipe.load_textual_inversion(text_encoder_2_sd, token=token_2, text_encoder=pipe.text_encoder_2, tokenizer=pipe.tokenizer_2) |
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pipe.load_lora_weights(os.path.join(folder, "lora.safetensors")) |
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pipe.to(torch_dtype=torch.float16) |
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pipe.to("cuda") |
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prompt="A <s0><s1> emoji of a man" |
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image = pipe(prompt, cross_attention_kwargs={"scale": 0.8}, num_inference_steps=20).images[0] |
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hiu.upload(image, "patrickvonplaten/images") |
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