---
license: apache-2.0
datasets:
- google/docci
- google/imageinwords
language:
- en
library_name: transformers
pipeline_tag: image-text-to-text
tags:
- art
---

Fine-tuned version of PaliGemma 224x224 on [google/docci](https://huggingface.co/datasets/google/docci) and [google/imageinwords](https://huggingface.co/datasets/google/imageinwords) datasets.
```
pip install git+https://github.com/huggingface/transformers
```

```python
from transformers import AutoProcessor, PaliGemmaForConditionalGeneration
from PIL import Image
import requests
import torch

model_id = "gokaygokay/sd3-long-captioner"

url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/car.jpg?download=true"
image = Image.open(requests.get(url, stream=True).raw)

model = PaliGemmaForConditionalGeneration.from_pretrained(model_id).to('cuda').eval()
processor = AutoProcessor.from_pretrained(model_id)

## prefix
prompt = "caption en"
model_inputs = processor(text=prompt, images=image, return_tensors="pt").to('cuda')
input_len = model_inputs["input_ids"].shape[-1]

with torch.inference_mode():
    generation = model.generate(**model_inputs, max_new_tokens=256, do_sample=False)
    generation = generation[0][input_len:]
    decoded = processor.decode(generation, skip_special_tokens=True)
    print(decoded)
 
```

<!-- gokaygokay-citation -->
## Citation and attribution

This model release is maintained by [Gökay Aydoğan](https://orcid.org/0000-0002-2343-9433). If you reference this repository in academic work, please cite it as follows and also cite the upstream models, datasets, or projects it builds upon.

```bibtex
@software{aydogan2024sd3_long_captioner,
  author = {Aydoğan, Gökay},
  title = {{sd3-long-captioner}},
  year = {2024},
  publisher = {Hugging Face},
  url = {https://huggingface.co/gokaygokay/sd3-long-captioner},
  note = {Model repository; cite the base model and upstream datasets as required.}
}
```