Instructions to use na1taneja2821/diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use na1taneja2821/diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("na1taneja2821/diffusers") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 4,102 Bytes
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# ์ปค์คํ
ํ์ดํ๋ผ์ธ ๋ถ๋ฌ์ค๊ธฐ
[[open-in-colab]]
์ปค๋ฎค๋ํฐ ํ์ดํ๋ผ์ธ์ ๋
ผ๋ฌธ์ ๋ช
์๋ ์๋์ ๊ตฌํ์ฒด์ ๋ค๋ฅธ ํํ๋ก ๊ตฌํ๋ ๋ชจ๋ [`DiffusionPipeline`] ํด๋์ค๋ฅผ ์๋ฏธํฉ๋๋ค. (์๋ฅผ ๋ค์ด, [`StableDiffusionControlNetPipeline`]๋ ["Text-to-Image Generation with ControlNet Conditioning"](https://arxiv.org/abs/2302.05543) ํด๋น) ์ด๋ค์ ์ถ๊ฐ ๊ธฐ๋ฅ์ ์ ๊ณตํ๊ฑฐ๋ ํ์ดํ๋ผ์ธ์ ์๋ ๊ตฌํ์ ํ์ฅํฉ๋๋ค.
[Speech to Image](https://github.com/huggingface/diffusers/tree/main/examples/community#speech-to-image) ๋๋ [Composable Stable Diffusion](https://github.com/huggingface/diffusers/tree/main/examples/community#composable-stable-diffusion) ๊ณผ ๊ฐ์ ๋ฉ์ง ์ปค๋ฎค๋ํฐ ํ์ดํ๋ผ์ธ์ด ๋ง์ด ์์ผ๋ฉฐ [์ฌ๊ธฐ์์](https://github.com/huggingface/diffusers/tree/main/examples/community) ๋ชจ๋ ๊ณต์ ์ปค๋ฎค๋ํฐ ํ์ดํ๋ผ์ธ์ ์ฐพ์ ์ ์์ต๋๋ค.
ํ๋ธ์์ ์ปค๋ฎค๋ํฐ ํ์ดํ๋ผ์ธ์ ๋ก๋ํ๋ ค๋ฉด, ์ปค๋ฎค๋ํฐ ํ์ดํ๋ผ์ธ์ ๋ฆฌํฌ์งํ ๋ฆฌ ID์ (ํ์ดํ๋ผ์ธ ๊ฐ์ค์น ๋ฐ ๊ตฌ์ฑ ์์๋ฅผ ๋ก๋ํ๋ ค๋) ๋ชจ๋ธ์ ๋ฆฌํฌ์งํ ๋ฆฌ ID๋ฅผ ์ธ์๋ก ์ ๋ฌํด์ผ ํฉ๋๋ค. ์๋ฅผ ๋ค์ด, ์๋ ์์์์๋ `hf-internal-testing/diffusers-dummy-pipeline`์์ ๋๋ฏธ ํ์ดํ๋ผ์ธ์ ๋ถ๋ฌ์ค๊ณ , `google/ddpm-cifar10-32`์์ ํ์ดํ๋ผ์ธ์ ๊ฐ์ค์น์ ์ปดํฌ๋ํธ๋ค์ ๋ก๋ํฉ๋๋ค.
<Tip warning={true}>
๐ ํ๊น
ํ์ด์ค ํ๋ธ์์ ์ปค๋ฎค๋ํฐ ํ์ดํ๋ผ์ธ์ ๋ถ๋ฌ์ค๋ ๊ฒ์ ๊ณง ํด๋น ์ฝ๋๊ฐ ์์ ํ๋ค๊ณ ์ ๋ขฐํ๋ ๊ฒ์
๋๋ค. ์ฝ๋๋ฅผ ์๋์ผ๋ก ๋ถ๋ฌ์ค๊ณ ์คํํ๊ธฐ ์์ ๋ฐ๋์ ์จ๋ผ์ธ์ผ๋ก ํด๋น ์ฝ๋์ ์ ๋ขฐ์ฑ์ ๊ฒ์ฌํ์ธ์!
</Tip>
```py
from diffusers import DiffusionPipeline
pipeline = DiffusionPipeline.from_pretrained(
"google/ddpm-cifar10-32", custom_pipeline="hf-internal-testing/diffusers-dummy-pipeline"
)
```
๊ณต์ ์ปค๋ฎค๋ํฐ ํ์ดํ๋ผ์ธ์ ๋ถ๋ฌ์ค๋ ๊ฒ์ ๋น์ทํ์ง๋ง, ๊ณต์ ๋ฆฌํฌ์งํ ๋ฆฌ ID์์ ๊ฐ์ค์น๋ฅผ ๋ถ๋ฌ์ค๋ ๊ฒ๊ณผ ๋๋ถ์ด ํด๋น ํ์ดํ๋ผ์ธ ๋ด์ ์ปดํฌ๋ํธ๋ฅผ ์ง์ ์ง์ ํ๋ ๊ฒ ์ญ์ ๊ฐ๋ฅํฉ๋๋ค. ์๋ ์์ ๋ฅผ ๋ณด๋ฉด ์ปค๋ฎค๋ํฐ [CLIP Guided Stable Diffusion](https://github.com/huggingface/diffusers/tree/main/examples/community#clip-guided-stable-diffusion) ํ์ดํ๋ผ์ธ์ ๋ก๋ํ ๋, ํด๋น ํ์ดํ๋ผ์ธ์์ ์ฌ์ฉํ `clip_model` ์ปดํฌ๋ํธ์ `feature_extractor` ์ปดํฌ๋ํธ๋ฅผ ์ง์ ์ค์ ํ๋ ๊ฒ์ ํ์ธํ ์ ์์ต๋๋ค.
```py
from diffusers import DiffusionPipeline
from transformers import CLIPImageProcessor, CLIPModel
clip_model_id = "laion/CLIP-ViT-B-32-laion2B-s34B-b79K"
feature_extractor = CLIPImageProcessor.from_pretrained(clip_model_id)
clip_model = CLIPModel.from_pretrained(clip_model_id)
pipeline = DiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
custom_pipeline="clip_guided_stable_diffusion",
clip_model=clip_model,
feature_extractor=feature_extractor,
)
```
์ปค๋ฎค๋ํฐ ํ์ดํ๋ผ์ธ์ ๋ํ ์์ธํ ๋ด์ฉ์ [์ปค๋ฎค๋ํฐ ํ์ดํ๋ผ์ธ](https://github.com/huggingface/diffusers/blob/main/docs/source/en/using-diffusers/custom_pipeline_examples) ๊ฐ์ด๋๋ฅผ ์ดํด๋ณด์ธ์. ์ปค๋ฎค๋ํฐ ํ์ดํ๋ผ์ธ ๋ฑ๋ก์ ๊ด์ฌ์ด ์๋ ๊ฒฝ์ฐ [์ปค๋ฎค๋ํฐ ํ์ดํ๋ผ์ธ์ ๊ธฐ์ฌํ๋ ๋ฐฉ๋ฒ](https://github.com/huggingface/diffusers/blob/main/docs/source/en/using-diffusers/contribute_pipeline)์ ๋ํ ๊ฐ์ด๋๋ฅผ ํ์ธํ์ธ์ ! |