Instructions to use tazumii/modeng-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tazumii/modeng-v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tazumii/modeng-v1", 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 text_encoder/pytorch_model.bin from tazumii/modeng-v1: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/tazumii/modeng-v1/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://tazumii/modeng-v1/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tazumii/modeng-v1/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- ef27f6d73da9a67ba94ef921cd77132b06c6fd9a834905baff6a7c815b2497ad
- Size of remote file:
- 246 MB
- SHA256:
- 88334ad317d834f831b4865bcd8c2ab10c32dff7c007be88c89af930c4c28c50
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