Instructions to use PRAMAY3000/floor-plan-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PRAMAY3000/floor-plan-generation with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("PRAMAY3000/floor-plan-generation", 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 PRAMAY3000/floor-plan-generation: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/PRAMAY3000/floor-plan-generation/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://PRAMAY3000/floor-plan-generation/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/PRAMAY3000/floor-plan-generation/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- ab7ce6e9d694e492897f4ede6ccfda7c78ed1ff94c521220a5c5e27f63a96ad3
- Size of remote file:
- 492 MB
- SHA256:
- 167b6a2833f6fc89f943171d8017d5c4d6b1a7c8b0d69a8f6f95447174daa094
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.