Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
diffusers-training
lora
Instructions to use yashvoladoddi37/kanji-diffusion-v1-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yashvoladoddi37/kanji-diffusion-v1-5 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", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("yashvoladoddi37/kanji-diffusion-v1-5") 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
LoRA text2image fine-tuning - yashvoladoddi37/kanji-diffusion-v1-5
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the yashvoladoddi37/kanjienglish dataset. You can find some example images in the following.
How to use
from diffusers import StableDiffusionPipeline
import torch
model_path = "yashvoladoddi37/kanji-diffusion-v1-5"
pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16, use_safetensors = True).to("cuda")
pipe.unet.load_attn_procs(model_path)
pipe.to("cuda")
prompt = "a Kanji meaning YouTube"
image = pipe(prompt).images[0]
image.save("youtube-kanji-v1-4.png")
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Model tree for yashvoladoddi37/kanji-diffusion-v1-5
Base model
runwayml/stable-diffusion-v1-5


