---
base_model: KHongJae/full_train_TE_D_0_10000to50000
library_name: diffusers
license: creativeml-openrail-m
tags:
- text-to-image
- dreambooth
- diffusers-training
- stable-diffusion
- stable-diffusion-diffusers
inference: true
---

<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->


# KHongJae/Chatting_Based_Emoji_Generation_Model

T-Academy ASAC 6기 DL 프로젝트에서 사용한 이모티콘 생성 모델입니다.

기존 묘사형 프롬프트에서만 작동 하던 Stable Diffusion을 대화형 프롬프트에서 작동할 수 있도록 시도한 모델입니다.




DreamBooth for the text encoder was enabled: True.


## Intended uses & limitations

![img_0](./png1.png)
![img_1](./png2.png)
![img_2](./png3.png)

#### How to use

```python
pipeline = DiffusionPipeline.from_pretrained(
    "KHongJae/Chatting_Based_Emoji_Generation_Model",
    torch_dtype=torch.float16
).to("cuda")
pipeline.scheduler = UniPCMultistepScheduler.from_config(pipeline.scheduler.config)
prompt = "Create your own prompt"
negative_prompt = "Create your own negative prompt"

pipeline(
  prompt=prompt,
  negative_prompt=negative_prompt,
  width=200,
  height=200,
  num_inference_steps=50,
  num_images_per_prompt=1,
  generator=torch.manual_seed(123456789),
).images[0]
```

#### Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

## Training details

[TODO: describe the data used to train the model]