Instructions to use Dascer/albahi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Dascer/albahi with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Dascer/albahi", 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 Dascer/albahi: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/Dascer/albahi/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Dascer/albahi@refs/pr/2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Dascer/albahi/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- a153406fd2290769780a13a3ad9baea9555200f67c4b2e7a652fb41ce5dd84e9
- Size of remote file:
- 246 MB
- SHA256:
- 17f4f3bc0322e8afa53d94de28a873484ff49ae62fa6504edc482303eab9a498
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