Add model card and metadata

Hi! I'm Niels from the Hugging Face community science team. I noticed that this repository currently lacks a model card. I've created this PR to add a README that includes relevant metadata, such as the pipeline tag and a link to your paper, along with usage instructions derived from your GitHub repository. This will help make your work more discoverable and easier for others to use.

README.md

@@ -0,0 +1,39 @@
+---
+pipeline_tag: image-segmentation
+---
+
+# InstructSAM: Segment Any Instance with Any Instructions
+
+InstructSAM is a unified and streamlined framework designed for multi-instance segmentation under arbitrary instructions. It formulates instruction-driven instance segmentation as a set-structured query prediction problem, bridging a vision-language model (VLM) and SAM3. This design equips SAM3 with high-level instruction understanding and compositional reasoning without modifying its core architecture.
+
+- **Paper:** [InstructSAM: Segment Any Instance with Any Instructions](https://huggingface.co/papers/2605.26102)
+- **Repository:** [https://github.com/DCDmllm/InstructSAM](https://github.com/DCDmllm/InstructSAM)
+
+## Usage
+
+To use this model, please refer to the [official repository](https://github.com/DCDmllm/InstructSAM) for environment setup and installation. 
+
+You can run single-image inference using the provided inference script:
+
+```bash
+python3 -m instructsam.infer \
+  --model_path CircleRadon/InstructSAM-2B \
+  --image-path path/to/image.jpg \
+  --query "Please segment the object in the image." \
+  --output-dir vis
+```
+
+The script prints the generated text and mask scores, then writes mask overlays to `vis/`.
+
+## Citation
+
+If you find this project useful, please cite using this BibTeX:
+
+```bibtex
+@article{yuan2026instructsam,
+  title     = {InstructSAM: Segment Any Instance with Any Instructions},
+  author    = {Yuqian Yuan, Wentong Li, Zhaocheng Li Yutong Lin, Juncheng Li, Siliang Tang, Jun Xiao, Yueting Zhuang, Wenqiao Zhang},
+  year      = {2026},
+  journal   = {arXiv},
+}
+```