Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionInstructPix2PixPipeline
stable-diffusion
stable-diffusion-diffusers
instruct-pix2pix
diffusers-training
lora
Instructions to use karel-ml6/indu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use karel-ml6/indu with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("karel-ml6/pix2pix", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("karel-ml6/indu") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
LoRA text2image fine-tuning - karel-ml6/indu
These are LoRA adaption weights for karel-ml6/pix2pix. The weights were fine-tuned on the None dataset. You can find some example images in the following.
Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
Training details
[TODO: describe the data used to train the model]
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Model tree for karel-ml6/indu
Base model
karel-ml6/pix2pix