Update README.md

README.md

@@ -1455,22 +1455,53 @@ MultiPL-E now supports Dart, thanks to [Devon Carew](https://github.com/devoncar
 
 This is the first significant update since MultiPL-E was used in StarCoder 1.
 
-1. We no longer publish the MultiPL-E ablations, but they are available in
+1. The dataset was versioned at 3.0, and we are bumping the software version to stay in sync.
+2. We no longer publish the MultiPL-E ablations, but they are available in
    revision `d23b094` and earlier.
-2. New programming languages supported:
+3. New programming languages supported:
    - Clojure, thanks to [Alex Miller](https://github.com/puredanger)
    - Elixir, thanks to [Marko Vukovic](https://github.com/mvkvc)
    - Haskell, thanks to [Thomas Dwyer](https://github.com/Cajunvoodoo)
    - OCaml, thanks to [John Gouwar](https://johngouwar.github.io)
-3. Changes to existing HumanEval-based problems:
+4. Changes to existing HumanEval-based problems:
    - Four Scala problems have fixed prompts/tests (12, 90, 128, 162).
    - Some whitespace-only changes to problems for Racket (18 problems),
      R (36 problems), Julia (159 problems), and D (156 problems). We will try to
      avoid these kinds of changes in the future.
-1. The MBPP-based problems have changes analogous to the HumanEval-based problems.
-
+5. The MBPP-based problems have changes analogous to the HumanEval-based problems.
+   
 See the directory `diffs_v3.0` in the dataset repository for the diffs to
 each prompt.
 
+### Version 0.5.0
+
+Instruction-following support and new languages
+
+  - New languages: Luau, Elixir, Lean, Coq, Dafny
+  - Support for instruction-following prompts
+  - vLLM support for faster evaluation
+
+### Version 0.4.0
+
+QoL improvements and new languages
+
+  - New languages: OCaml, MATLAB
+  - Using `.jsonl` instead of `.json` for prompts
+  - Several bugfixes to prompts
+
+### Version 0.3.0
+
+- This version was used to evaluate [StarCoder]
+
+- This version corrects several bugs in prompts and test cases that resulted in lower
+  pass@k rates for some of the statically typed languages. The most significant difference
+  is that the pass@k for Java increases by about 2% on HumanEval.
+
+### Version 0.2.0
+
+This version was used to evaluate [SantaCoder]
+
+[SantaCoder]: https://arxiv.org/abs/2301.03988
+[StarCoder]: https://arxiv.org/abs/2305.06161
 [BigCode Code Generation LM Harness]: https://github.com/bigcode-project/bigcode-evaluation-harness
 [MultiPL-E tutorial]: https://nuprl.github.io/MultiPL-E/