Instructions to use ayan4m1/trinart_diffusers_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ayan4m1/trinart_diffusers_v2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ayan4m1/trinart_diffusers_v2", 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
Download vae/diffusion_pytorch_model.bin from ayan4m1/trinart_diffusers_v2: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/ayan4m1/trinart_diffusers_v2/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://ayan4m1/trinart_diffusers_v2/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/ayan4m1/trinart_diffusers_v2/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- f6a7113b9e741e89312a70715364a56c314bc17ae6b5804015604dda34b35491
- Size of remote file:
- 335 MB
- SHA256:
- b8cf5b49d164db18a485d392b2d9a9b4e3636d70613cb756d2e1bc460dd13161
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