Instructions to use TIGER-Lab/ABC-Qwen2VL-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use TIGER-Lab/ABC-Qwen2VL-Instruct with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-VL-7B-Instruct") model = PeftModel.from_pretrained(base_model, "TIGER-Lab/ABC-Qwen2VL-Instruct") - Notebooks
- Google Colab
- Kaggle
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base_model: Qwen/Qwen2-VL-7B-Instruct
language:
- en
library_name: peft
license: mit
tags:
- LLM
- VLM
- Embedding
- Multimodal
pipeline_tag: image-text-to-text
---
```markdown
## Model Details
Instruction finetuned adapter for ABC: Acheiving Better Control of Multiomodal Embeddings using VLMs.
### Model Sources
This model is trained on top of Qwen2VL-Instruct.
### Paper and Website
For more information, please refer to [Website](https://tiger-ai-lab.github.io/ABC/).
## Citation
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
```
@misc{schneider2025abcachievingbettercontrol,
title={ABC: Achieving Better Control of Multimodal Embeddings using VLMs},
author={Benjamin Schneider and Florian Kerschbaum and Wenhu Chen},
year={2025},
eprint={2503.00329},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2503.00329},
}
```
``` |