Instructions to use lovis93/testllm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lovis93/testllm with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lovis93/testllm", 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

- Xet hash:
- 62c632ec8d34195089dc7872f135dfab07e6e7ffbd7b792c883b4aaba8b7ac58
- Size of remote file:
- 1.3 MB
- SHA256:
- 37a587d0ff3d9dda0d8ab59d65342c0242ffb909573d8d998d599e3401d3d7e9
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