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---
license: mit
---
# Official ICC model
The official checkpoint of ICC model, introduced in [ICC: Quantifying Image Caption Concreteness for Multimodal Dataset Curation](https://arxiv.org/abs/2403.01306)
[Project Page](https://moranyanuka.github.io/icc/)
## Usage
The ICC model is used to quantify the concreteness of image captions (and sentences in general).
### Running the model
<details>
<summary> Click to expand </summary>
```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
tokenizer = AutoTokenizer.from_pretrained("moranyanuka/icc")
model = AutoModelForSequenceClassification.from_pretrained("moranyanuka/icc").to("cuda")
captions = ["a great method of quantifying concreteness", "a man with a white shirt"]
text_ids = tokenizer(captions, padding=True, return_tensors="pt", truncation=True).to('cuda')
with torch.inference_mode():
icc_scores = model(**text_ids)['logits']
# tensor([[0.0339], [1.0068]])
```
</details>
bibtex:
```
@misc{yanuka2024icc,
title={ICC: Quantifying Image Caption Concreteness for Multimodal Dataset Curation},
author={Moran Yanuka and Morris Alper and Hadar Averbuch-Elor and Raja Giryes},
year={2024},
eprint={2403.01306},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
``` |