Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
trl
ddpo
reinforcement-learning
stable-diffusion
Instructions to use Nguyen17/Diff1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Nguyen17/Diff1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Nguyen17/Diff1", 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
| license: apache-2.0 | |
| tags: | |
| - trl | |
| - ddpo | |
| - diffusers | |
| - reinforcement-learning | |
| - text-to-image | |
| - stable-diffusion | |
| # TRL DDPO Model | |
| This is a diffusion model that has been fine-tuned with reinforcement learning to | |
| guide the model outputs according to a value, function, or human feedback. The model can be used for image generation conditioned with text. | |