Instructions to use hdparmar/tradfusion-e5-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hdparmar/tradfusion-e5-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hdparmar/tradfusion-e5-diffusers", 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
Download last-checkpoint from hdparmar/tradfusion-e5-diffusers: direct link, hf CLI and curl.
- Browser
- Download file 14.6 GB
-
https://huggingface.co/hdparmar/tradfusion-e5-diffusers/resolve/main/last-checkpoint
- Command line
-
hf download hf://hdparmar/tradfusion-e5-diffusers/last-checkpoint
-
curl -L -o last-checkpoint https://huggingface.co/hdparmar/tradfusion-e5-diffusers/resolve/main/last-checkpoint
14.6 GB
- Xet hash:
- 22902a78ce555db4f716b0ec19c5e0ced785f57a3ffd93bca073ec3ad074f883
- Size of remote file:
- 14.6 GB
- SHA256:
- 90594bc9fdeb3d27081985969f056978edff70d775c19df54d6cadf3cb5d6fcb
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