Instructions to use ahpf2016/aishabh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ahpf2016/aishabh with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ahpf2016/aishabh", 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 ahpf2016/aishabh: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/ahpf2016/aishabh/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://ahpf2016/aishabh@refs/pr/2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ahpf2016/aishabh/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 79d48ee60f211a33f2acdc3290253b9c8bf68379ff5c77220195f61190a3a877
- Size of remote file:
- 492 MB
- SHA256:
- f725396a495ed182ba1597eed9a8857a1ad2ec2a620d010fdda4e173be597cb9
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