Add model card and metadata

Hi! I'm Niels from the Hugging Face community team. I noticed that this repository didn't have a model card, so I've opened this PR to add one. It includes relevant metadata like the pipeline tag, library name, and base model, as well as links to the paper and GitHub repository to make the model more discoverable.

README.md

@@ -1,3 +1,35 @@
----
-license: mit
----
+---
+license: mit
+library_name: transformers
+base_model: Qwen/Qwen3-Reranker-0.6B
+pipeline_tag: text-generation
+tags:
+- code
+- context-pruning
+---
+
+# SWE-Pruner: Self-Adaptive Context Pruning for Coding Agents
+
+SWE-Pruner is a self-adaptive context pruning framework specifically designed for coding agents. It addresses the challenges of long interaction contexts, such as high API costs and latency, by performing task-aware adaptive pruning.
+
+- **Paper:** [SWE-Pruner: Self-Adaptive Context Pruning for Coding Agents](https://huggingface.co/papers/2601.16746)
+- **Repository:** [https://github.com/Ayanami1314/swe-pruner](https://github.com/Ayanami1314/swe-pruner)
+
+## Description
+Inspired by how human programmers selectively skim code, SWE-Pruner enables agents to formulate explicit goals (e.g., "focus on error handling") which guide a lightweight neural skimmer (0.6B parameters). This skimmer dynamically selects relevant lines from the surrounding context, preserving critical implementation details while significantly reducing token usage.
+
+Evaluations across benchmarks show that SWE-Pruner achieves 23-54% token reduction on agent tasks like SWE-Bench Verified and up to 14.84x compression on single-turn tasks like LongCodeQA with minimal performance impact.
+
+## Citation
+If you find SWE-Pruner useful in your research, please cite:
+```bibtex
+@misc{wang2026sweprunerselfadaptivecontextpruning,
+      title={SWE-Pruner: Self-Adaptive Context Pruning for Coding Agents}, 
+      author={Yuhang Wang and Yuling Shi and Mo Yang and Rongrui Zhang and Shilin He and Heng Lian and Yuting Chen and Siyu Ye and Kai Cai and Xiaodong Gu},
+      year={2026},
+      eprint={2601.16746},
+      archivePrefix={arXiv},
+      primaryClass={cs.SE},
+      url={https://arxiv.org/abs/2601.16746},
+}
+```