Release v0.1.3

Author: Luciennnnnnn

.gitignore

@@ -233,4 +233,7 @@ outputs_gradio/*
 test.py
 
 upload_to_huggingface.py
-upload_to_modelscope.py
+upload_to_modelscope.py
+
+editscore.egg-info/
+dist/

README.md

@@ -26,6 +26,7 @@
 - **Versatile Applications**: Ready to use as a best-in-class reranker to improve editing outputs, or as a high-fidelity reward signal for **stable and effective Reinforcement Learning (RL) fine-tuning**.
 
 ## 🔥 News
+- **2025-10-15**: **EditScore** is now available on PyPI — install it easily with `pip install editscore`.
 - **2025-10-15**: Best-of-N inference scripts for OmniGen2, Flux-dev-Kontext, and Qwen-Image-Edit are now available! See [this](#apply-editscore-to-image-editing) for details.
 - 2025-09-30: We release **OmniGen2-EditScore7B**, unlocking online RL For Image Editing via high-fidelity EditScore. LoRA weights are available at [Hugging Face](https://huggingface.co/OmniGen2/OmniGen2-EditScore7B) and [ModelScope](https://www.modelscope.cn/models/OmniGen2/OmniGen2-EditScore7B).
 - 2025-09-30: We are excited to release **EditScore** and **EditReward-Bench**! Model weights and the benchmark dataset are now publicly available. You can access them on Hugging Face: [Models Collection](https://huggingface.co/collections/EditScore/editscore-68d8e27ee676981221db3cfe) and [Benchmark Dataset](https://huggingface.co/datasets/EditScore/EditReward-Bench), and on ModelScope: [Models Collection](https://www.modelscope.cn/collections/EditScore-8b0d53aa945d4e) and [Benchmark Dataset](https://www.modelscope.cn/datasets/EditScore/EditReward-Bench).

examples/OmniGen2-RL/docs/README.md

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "editscore"
-version = "0.1.2"
+version = "0.1.3"
 authors = [
   { name="Xin Luo", email="[email protected]" },
   { name="Jiahao Wang", email="[email protected]" },