Instructions to use BreakpointAI/socknet3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BreakpointAI/socknet3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BreakpointAI/socknet3", 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
File size: 1,211 Bytes
4f6ef57 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | ---
library_name: diffusers
license: other
license_name: research-use
tags:
- object-detection
- bounding-boxes
- grounding
- diffusion
- synthetic-data
---
# socknet3
Joint image + bounding-box diffusion model with a LoRA adapter.
Released by [Breakpoint AI](https://huggingface.co/BreakpointAI) as part of open-sourcing the company's research
artifacts.
| | |
|---|---|
| Training data | [`BreakpointAI/breakpoint-grounding-55m`](https://huggingface.co/datasets/BreakpointAI/breakpoint-grounding-55m) |
| Checkpoint step | 625,000 |
| Training run | [W&B](https://wandb.ai/diffusionexp/creati_socknet/runs/qzgqqmhh) |
## Contents
| Path | Size | What it is |
|---|---|---|
| `boxnet/` | 3.9 GB | Joint image + bounding-box diffusion backbone |
| `pytorch_lora_weights.safetensors` | 305.2 MB | LoRA adapter weights |
**Inference weights only.** Optimizer, LR scheduler, RNG and dataloader state were not
uploaded, so this checkpoint cannot be used to resume training.
## Citation
```bibtex
@misc{breakpoint_socknet3,
title = {socknet3},
author = {Wang, Franklin and Zhong, Desmond and Murdoch, Jamie},
year = {2026},
url = {https://huggingface.co/BreakpointAI/socknet3}
}
```
|