Instructions to use jrjyc1/trainee with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jrjyc1/trainee with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jrjyc1/trainee", 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
- Draw Things
- DiffusionBee
| language: | |
| - "List of ISO 639-1 code for your language" | |
| - lang1 | |
| - lang2 | |
| thumbnail: "url to a thumbnail used in social sharing" | |
| tags: | |
| - tag1 | |
| - tag2 | |
| license: "any valid license identifier" | |
| datasets: | |
| - dataset1 | |
| - dataset2 | |
| metrics: | |
| - metric1 | |
| - metric2 | |