Instructions to use pakuschj/janbrv170582 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use pakuschj/janbrv170582 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("pakuschj/janbrv170582", dtype=torch.bfloat16, device_map="cuda") prompt = "janbrv170582" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from pakuschj/janbrv170582: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/pakuschj/janbrv170582/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://pakuschj/janbrv170582/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/pakuschj/janbrv170582/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 46a22ed07b375b3541673ea25f0ce693bfefdaea4cb045fe621e60a31cddb5fe
- Size of remote file:
- 492 MB
- SHA256:
- 5f06bcdbbf138061cb2f35d02cb67d9ba49eaf0ca627f9facba4bdb01ef6c8e6
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