Instructions to use rynmurdock/CLIP_DRaFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rynmurdock/CLIP_DRaFT 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("rynmurdock/CLIP_DRaFT") prompt = "a horse with many eyes" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: a horse with many eyes
output:
url: images/a horse with many eyes.png
base_model: runwayml/stable-diffusion-v1-5
instance_prompt: null
CLIP_DRaFT

- Prompt
- a horse with many eyes
Model description
Made from my implementation of DRaFT using CLIP.
Download model
Weights for this model are available in Safetensors format.