Instructions to use erkam/sg2im-256-bs-16x2-lr1e4-depth-snr-12k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use erkam/sg2im-256-bs-16x2-lr1e4-depth-snr-12k with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("erkam/sg2im-256-bs-16x2-lr1e4-depth-snr-12k") 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
Download checkpoint-20000/pytorch_lora_weights.bin from erkam/sg2im-256-bs-16x2-lr1e4-depth-snr-12k: direct link, hf CLI and curl.
- Browser
- Download file 3.42 MB
-
https://huggingface.co/erkam/sg2im-256-bs-16x2-lr1e4-depth-snr-12k/resolve/main/checkpoint-20000/pytorch_lora_weights.bin
- Command line
-
hf download hf://erkam/sg2im-256-bs-16x2-lr1e4-depth-snr-12k/checkpoint-20000/pytorch_lora_weights.bin
-
curl -L -o pytorch_lora_weights.bin https://huggingface.co/erkam/sg2im-256-bs-16x2-lr1e4-depth-snr-12k/resolve/main/checkpoint-20000/pytorch_lora_weights.bin
3.42 MB
- Xet hash:
- fa6af207c1c7fd8b13919abd97dd437ae8277de2f304e043576fcbe71023eabf
- Size of remote file:
- 3.42 MB
- SHA256:
- e8c23536a3bab214c2aedc56817bd3c6e01a8866243b4ec89f89a118505499cc
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