---
library_name: transformers
license: cc-by-nc-4.0
datasets:
- histai/SPIDER-colorectal
base_model:
- histai/hibou-L
pipeline_tag: image-classification
---

# SPIDER-Colorectal Model


### Model Description

SPIDER-colorectal model is a deep learning model trained for patch-level pathology classification, specifically for colorectal. It is part of the SPIDER dataset initiative, which provides a large, high-quality, multi-organ pathology dataset with expert-annotated labels.

If you would like to support, sponsor, or obtain a commercial license for the SPIDER data and models, please contact us at models@hist.ai.
### Model Sources

- **Repository:** [https://github.com/HistAI/SPIDER](https://github.com/HistAI/SPIDER)
- **Paper:** [SPIDER: A Comprehensive Multi-Organ Supervised Pathology Dataset and Baseline Models](https://arxiv.org/abs/2503.02876)

## How to Get Started with the Model

Model works with **1120×1120** patches.
Use the following code snippet to load and use the model:

```python
from transformers import AutoModel, AutoProcessor
from PIL import Image

model = AutoModel.from_pretrained("histai/SPIDER-colorectal-model", trust_remote_code=True)
processor = AutoProcessor.from_pretrained("histai/SPIDER-colorectal-model", trust_remote_code=True)

image = Image.open("path_to_image.png")
inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)
print(outputs.predicted_class_names)
```


### Training Data

The model is trained on the [SPIDER-colorectal](https://huggingface.co/datasets/histai/SPIDER-colorectal) dataset, a subset of the SPIDER dataset. The dataset includes:

| Class                         | Central Patches |
|--------------------------------|------------|
| Adenocarcinoma high grade      | 6299       |
| Adenocarcinoma low grade       | 6066       |
| Adenoma high grade             | 5493       |
| Adenoma low grade              | 5693       |
| Fat                            | 6081       |
| Hyperplastic polyp             | 5893       |
| Inflammation                   | 5523       |
| Mucus                          | 5711       |
| Muscle                         | 5866       |
| Necrosis                       | 5481       |
| Sessile serrated lesion        | 4993       |
| Stroma healthy                 | 8001       |
| Vessels                        | 6082       |

**Total Counts:**
- **77,182** central patches
- **1,039,150** total patches (including context patches)
- **1,719** total slides used for annotation

### Results

| Organ   | Accuracy | Precision | F1 Score |
|---------|----------|------------|----------|
| Colorectal  | 0.914    | 0.917      | 0.915    |

## License
The model is licensed under **CC BY-NC 4.0** and is for **research use only**.

## Citation
If you use this model, please cite the following:

```bibtex
@misc{nechaev2025spidercomprehensivemultiorgansupervised,
      title={SPIDER: A Comprehensive Multi-Organ Supervised Pathology Dataset and Baseline Models}, 
      author={Dmitry Nechaev and Alexey Pchelnikov and Ekaterina Ivanova},
      year={2025},
      eprint={2503.02876},
      archivePrefix={arXiv},
      primaryClass={eess.IV},
      url={https://arxiv.org/abs/2503.02876}, 
}
```

## More Information

To explore other models and the SPIDER dataset you can visit the [Hugging Face HistAI page](https://huggingface.co/histai) or [GitHub](https://github.com/HistAI/SPIDER) of the project.

## Contacts

- **Authors:** Dmitry Nechaev, Alexey Pchelnikov, Ekaterina Ivanova
- **Email:** dmitry@hist.ai, alex@hist.ai, kate@hist.ai