Instructions to use coder119/Vectorartz_Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use coder119/Vectorartz_Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("coder119/Vectorartz_Diffusion", 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 coder119/Vectorartz_Diffusion: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/coder119/Vectorartz_Diffusion/resolve/568a6d679ca2f347e78f2e80a5abe18c442531da/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://coder119/Vectorartz_Diffusion@568a6d679ca2f347e78f2e80a5abe18c442531da/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/coder119/Vectorartz_Diffusion/resolve/568a6d679ca2f347e78f2e80a5abe18c442531da/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- d6908876b67a874e9ab1dd1f2b090687cf700bdb9b1b9018d8accdf4bf76eb69
- Size of remote file:
- 492 MB
- SHA256:
- f3f4a24ea86b32e2ab91c035bd3377777bc71dc71102906625e3266025150580
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