Image-Text-to-Text
PEFT
Safetensors
English
remote-sensing
temporal-understanding
multimodal
lora
earth-observation
qwen3-vl
conversational
Instructions to use Davidup1/GeoChrono with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Davidup1/GeoChrono with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-VL-4B-Instruct") model = PeftModel.from_pretrained(base_model, "Davidup1/GeoChrono") - Notebooks
- Google Colab
- Kaggle
Add project page link
Browse files
README.md
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GeoChrono is introduced in the paper [*GeoChrono: Benchmarking and Rethinking Long-Term Temporal Understanding in Remote Sensing*](https://arxiv.org/abs/2607.15768) (**accepted at ACM MM 2026** π₯), together with the **ChronoBench** benchmark and the **ChronoInstruct** instruction-tuning dataset.
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- π **Paper**: https://arxiv.org/abs/2607.15768
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- π¦ **Code**: https://github.com/IntelliSensing/GeoChrono
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- π **Data (ChronoBench & ChronoInstruct)**: https://huggingface.co/datasets/Davidup1/GeoChrono-Data
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GeoChrono is introduced in the paper [*GeoChrono: Benchmarking and Rethinking Long-Term Temporal Understanding in Remote Sensing*](https://arxiv.org/abs/2607.15768) (**accepted at ACM MM 2026** π₯), together with the **ChronoBench** benchmark and the **ChronoInstruct** instruction-tuning dataset.
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- π **Paper**: https://arxiv.org/abs/2607.15768
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- π **Project Page**: https://davidup1.github.io/papers/geochrono/
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- π¦ **Code**: https://github.com/IntelliSensing/GeoChrono
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- π **Data (ChronoBench & ChronoInstruct)**: https://huggingface.co/datasets/Davidup1/GeoChrono-Data
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