diff --git a/README.md b/README.md index 1a993d0c2b6736e5c57e252a74c2fd9024b444fc..d51993f7a4e0308f56a574ea7a4c6633b644c643 100644 --- a/README.md +++ b/README.md @@ -1312,50 +1312,28 @@ These are the prompt variations: Note that MBPP does not have any doctests, so the "removed" and "transform" variations are not available for MBPP. -## Example Script +## Changelog -The following script uses the Salesforce/codegen model to generate Lua -and MultiPL-E to produce a script with unit tests for luaunit. -*This example is quite outdated.* +### Version 3.0 -```python -import datasets -from transformers import AutoTokenizer, AutoModelForCausalLM +This is the first significant update since MultiPL-E was used in StarCoder 1. -LANG = "lua" -MODEL_NAME = "Salesforce/codegen-350M-multi" -tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME) -model = AutoModelForCausalLM.from_pretrained(MODEL_NAME).half().cuda() -problems = datasets.load_dataset("nuprl/MultiPL-E", f"humaneval-{LANG}") +1. We no longer publish the MultiPL-E ablations, but they are available in + revision `d23b094` and earlier. +2. 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 https://github.com/Cajunvoodoo + - OCaml, thanks to [John Gouwar](https://johngouwar.github.io) +3. 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. -def stop_at_stop_token(decoded_string, problem): - """ - Truncates the output at stop tokens, taking care to skip the prompt - which may have stop tokens. - """ - min_stop_index = len(decoded_string) - for stop_token in problem["stop_tokens"]: - stop_index = decoded_string.find(stop_token) - if stop_index != -1 and stop_index > len(problem["prompt"]) and stop_index < min_stop_index: - min_stop_index = stop_index - return decoded_string[:min_stop_index] - -for problem in problems["test"]: - input_ids = tokenizer( - problem["prompt"], - return_tensors="pt", - ).input_ids.cuda() - generated_ids = model.generate( - input_ids, max_length=512, pad_token_id=tokenizer.eos_token_id + 2 - ) - truncated_string = stop_at_stop_token(tokenizer.decode(generated_ids[0]), problem) - filename = problem["name"] + "." + LANG - with open(filename, "w") as f: - print(f"Created {filename}") - f.write(truncated_string) - f.write("\n") - f.write(problem["tests"]) -``` +See the directory `diffs_v3.0` in the dataset repository for the diffs to +each prompt. [BigCode Code Generation LM Harness]: https://github.com/bigcode-project/bigcode-evaluation-harness [MultiPL-E tutorial]: https://nuprl.github.io/MultiPL-E/ \ No newline at end of file diff --git a/diffs_v3.0/.gitattributes b/diffs_v3.0/.gitattributes new file mode 100644 index 0000000000000000000000000000000000000000..19f6a54fc517ac46b857d064b2466890b589b933 --- /dev/null +++ b/diffs_v3.0/.gitattributes @@ -0,0 +1 @@ +*.diff filter=lfs diff=lfs merge=lfs -text diff --git a/diffs_v3.0/humaneval-d_prompt_HumanEval_0_has_close_elements.diff b/diffs_v3.0/humaneval-d_prompt_HumanEval_0_has_close_elements.diff new file mode 100644 index 0000000000000000000000000000000000000000..85c935ee9a4ae1f0417e5c36791d9174cf419e88 --- /dev/null +++ b/diffs_v3.0/humaneval-d_prompt_HumanEval_0_has_close_elements.diff @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:db92fa300c8cd7bf08250d5a7c7d7bd14b0cb92949c412d776872fff9f618708 +size 534 diff --git 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