Instructions to use segmind/SSD-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use segmind/SSD-1B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("segmind/SSD-1B", 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
- Draw Things
- DiffusionBee
corrupted image outputs with safetensor
Getting a lot of glitchy artifacts on latest a11, is this an a11 upstream issue or is this an issue with the safetensor / model?
realistic photo of a panda sitting in a forest, waterfall, rain, bamboo Steps: 20, Sampler: Euler, CFG scale: 7, Seed: 312736957, Size: 1024x1024, Model hash: 0bf1ce6b06, Model: SSD-1B, VAE hash: 551eac7037, VAE: sdxl_vae_0.9.safetensors, Version: v1.6.0-263-g464fbcd9
realistic photo of a panda sitting in a forest, waterfall, rain, bamboo Steps: 20, Sampler: DPM++ 2M, CFG scale: 7, Seed: 255731624, Size: 1024x1024, Model hash: 0bf1ce6b06, Model: SSD-1B, VAE hash: 551eac7037, VAE: sdxl_vae_0.9.safetensors, Version: v1.6.0-263-g464fbcd9
tried without VAE too, but that didn't change it, same metadata on SDXL looks fine
Likely a safetensors ckpt error. We'll look into it.
converting via: https://github.com/huggingface/diffusers/blob/main/scripts/convert_diffusers_to_original_sdxl.py worked, might be worth re-doing for official .safetensor
We've used that only for the conversion, Will check and update soon.
We'll be adding A1111 compatibility soon. Thanks for reporting!
ComfyUI support has been added.
Automatic1111 support has been added, please use this checkpoint and tell if the artifacts still persist.
Fixed, nearly identical to my pruned version too, good job

