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--- |
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base_model: KHongJae/full_train_TE_D_0_10000to50000 |
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library_name: diffusers |
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license: creativeml-openrail-m |
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tags: |
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- text-to-image |
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- dreambooth |
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- diffusers-training |
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- stable-diffusion |
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- stable-diffusion-diffusers |
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inference: true |
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--- |
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<!-- This model card has been generated automatically according to the information the training script had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# KHongJae/Chatting_Based_Emoji_Generation_Model |
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T-Academy ASAC 6κΈ° DL νλ‘μ νΈμμ μ¬μ©ν μ΄λͺ¨ν°μ½ μμ± λͺ¨λΈμ
λλ€. |
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κΈ°μ‘΄ λ¬μ¬ν ν둬ννΈμμλ§ μλ νλ Stable Diffusionμ λνν ν둬ννΈμμ μλν μ μλλ‘ μλν λͺ¨λΈμ
λλ€. |
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DreamBooth for the text encoder was enabled: True. |
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## Intended uses & limitations |
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#### How to use |
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```python |
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pipeline = DiffusionPipeline.from_pretrained( |
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"KHongJae/Chatting_Based_Emoji_Generation_Model", |
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torch_dtype=torch.float16 |
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).to("cuda") |
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pipeline.scheduler = UniPCMultistepScheduler.from_config(pipeline.scheduler.config) |
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prompt = "Create your own prompt" |
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negative_prompt = "Create your own negative prompt" |
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pipeline( |
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prompt=prompt, |
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negative_prompt=negative_prompt, |
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width=200, |
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height=200, |
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num_inference_steps=50, |
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num_images_per_prompt=1, |
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generator=torch.manual_seed(123456789), |
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).images[0] |
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``` |
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#### Limitations and bias |
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[TODO: provide examples of latent issues and potential remediations] |
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## Training details |
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[TODO: describe the data used to train the model] |