Text-to-Image
Diffusers
TensorBoard
Safetensors
Sana
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
diffusers-training
lora
sana-diffusers
template:sd-lora
Instructions to use ainjarts/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ainjarts/output with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("darkstorm2150/Protogen_x3.4_Official_Release", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ainjarts/output") prompt = "a photo of ohwx woman" image = pipe(prompt).images[0] - Sana
How to use ainjarts/output with Sana:
# Load the model and infer image from text import torch from app.sana_pipeline import SanaPipeline from torchvision.utils import save_image sana = SanaPipeline("configs/sana_config/1024ms/Sana_1600M_img1024.yaml") sana.from_pretrained("hf://ainjarts/output") image = sana( prompt='a cyberpunk cat with a neon sign that says "Sana"', height=1024, width=1024, guidance_scale=5.0, pag_guidance_scale=2.0, num_inference_steps=18, ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- d319ed6db52682f769fc7a600adf238b6afefb04cd58314e73d18a638fa34c92
- Size of remote file:
- 22.1 MB
- SHA256:
- d5f104546cdbabfd56f253f71e371e2727011cd45114f1dca6f0c2e22886a8de
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