Instructions to use svjack/concept-caption-3m-sd-lora-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use svjack/concept-caption-3m-sd-lora-zh with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("svjack/concept-caption-3m-sd-lora-zh") 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
Model Card for svjack/concept-caption-3m-sd-lora-zh
Installation
pip install -U diffusers
pip install transformers
Usage
from diffusers import StableDiffusionPipeline
import torch
pipe = StableDiffusionPipeline.from_pretrained("IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1", torch_dtype=torch.float16)
model_path = "svjack/concept-caption-3m-sd-lora-zh"
pipe.unet.load_attn_procs(model_path)
pipe.to("cuda")
pipe.safety_checker = lambda images, clip_input: (images, False)
print("have_load")
prompt = "一只快乐的狗。"
image = pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]
image
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