Instructions to use OdyAsh/hf_diffusion_model_all_sample_classes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OdyAsh/hf_diffusion_model_all_sample_classes with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OdyAsh/hf_diffusion_model_all_sample_classes", 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
Merge branch 'main' of https://huggingface.co/OdyAsh/huggingface_diffusion_model
Browse files- logs/train_example/events.out.tfevents.1679894551.LAPTOP-RE72OONJ.26340.0 +3 -0
- logs/train_example/events.out.tfevents.1679898828.LAPTOP-RE72OONJ.26340.1 +3 -0
- logs/train_example/events.out.tfevents.1679898872.LAPTOP-RE72OONJ.26340.2 +3 -0
- logs/train_example/events.out.tfevents.1679899227.LAPTOP-RE72OONJ.26340.3 +3 -0
- logs/train_example/events.out.tfevents.1679899384.LAPTOP-RE72OONJ.26228.0 +3 -0
- samples/0009.png +2 -2
logs/train_example/events.out.tfevents.1679894551.LAPTOP-RE72OONJ.26340.0
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samples/0009.png
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