Instructions to use ULZIITOGTOKH/road_obstacles with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ULZIITOGTOKH/road_obstacles with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ULZIITOGTOKH/road_obstacles", 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 checkpoint-2000/optimizer.bin from ULZIITOGTOKH/road_obstacles: direct link, hf CLI and curl.
- Browser
- Download file 910 MB
-
https://huggingface.co/ULZIITOGTOKH/road_obstacles/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://ULZIITOGTOKH/road_obstacles/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/ULZIITOGTOKH/road_obstacles/resolve/main/checkpoint-2000/optimizer.bin
910 MB
- Xet hash:
- 863b7677cf1c69b4ba0dd0bf2d1b874c77b09d836dbbda4d8c1b1f3816cbc8ca
- Size of remote file:
- 910 MB
- SHA256:
- 979544c3153069531eb24ea176a72af4fb6e0339d8161f905c323636bd88191f
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