build: release v0.1.0 (#116)

Author: chrbrunk

.github/workflows/validate_pr_title.yaml

@@ -14,5 +14,5 @@ jobs:
       - name: "PR Conventional Commit Validation"
         uses: ytanikin/pr-conventional-commits@1.4.0
         with:
-          task_types: '["feat","fix","docs","test","ci","refactor","perf","chore","revert", "data"]'
+          task_types: '["feat","build","fix","docs","test","ci","refactor","perf","chore","revert", "data"]'
           add_label: 'false'

CHANGELOG.md

@@ -0,0 +1,11 @@
+# Changelog
+
+## Release 0.1.0
+
+- Adding benchmark implementations for 15 benchmarks.
+- Adding CLI tool that can (a) run benchmarks and (b) display a GUI for
+  visualization of benchmark results.
+- Adding code for public leaderboard page only displayed on the
+  HuggingFace leaderboard of MLIP models.
+- Adding extensive code documentation with tutorials.
+- Adding extensive unit test coverage.

README.md

@@ -6,11 +6,6 @@
 [![Tests and Linters](https://github.com/instadeepai/mlipaudit/actions/workflows/tests_and_linters_and_docs_build.yaml/badge.svg?branch=main)](https://github.com/instadeepai/mlipaudit/actions/workflows/tests_and_linters_and_docs_build.yaml)
 ![badge](https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/mlipbot/e7c79b17c0a9d47bc826100ef880a16f/raw/pytest-coverage-comment.json)
 
-## ⚠️ Disclaimer
-
-This repository is currently in pre-release mode. Official release of v0.1.0 will be
-communicated soon.
-
 ## 👀 Overview
 
 **MLIPAudit** is a Python library and app for benchmarking and
@@ -189,9 +184,9 @@ Massimo Bortone, Jack Sawdon, Olivier Peltre and Alex Laterre.
 
 ## 📚 Citing our work
 
-We kindly request that you to cite our white paper
+We kindly request that you to cite [our white paper](https://arxiv.org/abs/2511.20487)
 when using this library:
 
-L. Wehrhan, L. Walewski, M. Bluntzer, H. Chomet, C. Brunken, J.Tilly and
+L. Wehrhan, L. Walewski, M. Bluntzer, H. Chomet, J.Tilly, C. Brunken and
 S. Acosta-Gutiérrez, *MLIPAudit: A benchmarking tool for Machine
-Learned Interatomic Potentials*, soon on arXiv.
+Learned Interatomic Potentials*, arXiv, 2025, arXiv:2511.20487.

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "mlipaudit"
-version = "0.0.1a3"
+version = "0.1.0"
 description = "Library and CLI tool for benchmarking ML Interatomic Potentials"
 readme = "README.md"
 authors = [

src/mlipaudit/ui/leaderboard.py

@@ -139,9 +139,9 @@ def leaderboard_page(
         """
         MLIPAudit is a Python tool for benchmarking and validating
         Machine Learning Interatomic Potentials (MLIP) models,
-        specifically those written in mlip-jax. It aims to cover
-        a wide range of use cases and difficulties, providing users
-        with a comprehensive overview of the performance of their models.
+        specifically those based on the [mlip](https://github.com/instadeepai/mlip)
+        library. It aims to cover a wide range of use cases and difficulties, providing
+        users with a comprehensive overview of the performance of their models.
         """
     )