Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use KHongJae/Chatting_Based_Emoji_Generation_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KHongJae/Chatting_Based_Emoji_Generation_Model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("KHongJae/Chatting_Based_Emoji_Generation_Model", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
KHongJae/Chatting_Based_Emoji_Generation_Model
T-Academy ASAC 6๊ธฐ DL ํ๋ก์ ํธ์์ ์ฌ์ฉํ ์ด๋ชจํฐ์ฝ ์์ฑ ๋ชจ๋ธ์
๋๋ค.
๊ธฐ์กด ๋ฌ์ฌํ ํ๋กฌํํธ์์๋ง ์๋ ํ๋ Stable Diffusion์ ๋ํํ ํ๋กฌํํธ์์ ์๋ํ ์ ์๋๋ก ์๋ํ ๋ชจ๋ธ์
๋๋ค.
Intended uses & limitations
- prompt : 'ํ๋ ๊ท๋ฅผ ๊ฐ์ง ๊ณ ์์ด, ์ด๋ชจํฐ์ฝ, ๋จ์ ๋ฐฐ๊ฒฝ, ๋์ ํธ ๋จน๋ ์ค!'
How to use
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
).images[0]
Training details
- ์นด์นด์คํก ์ด๋ชจํฐ์ฝ ๋ฐ์ดํฐ
- ChatGPT4
- Downloads last month
- -
Model tree for KHongJae/Chatting_Based_Emoji_Generation_Model
Base model
kyujinpy/KO-anything-v4-5 Finetuned
KHongJae/full_train_TE_D_0to10000 Finetuned
KHongJae/full_train_TE_D_0_10000to50000

