Instructions to use jayavibhav/trial-jv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jayavibhav/trial-jv with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jayavibhav/trial-jv", dtype=torch.bfloat16, device_map="cuda") 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
Stable Diffusion fine-tuned model version 1.5_1
Trained on custom dataset of cyberpunk themed images, dataset - https://drive.google.com/drive/folders/10BqmKMpzPeYrY78HBL2gBfFDjwf0g_oL?usp=drive_link (3000 images)
Custom created for project Unifactory - https://devfolio.co/projects/unifactory-a553
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