23ws-LLMcoder/LLMcoder-GitHub-Python-Mix-Direct
Dataset Card for LLMcoder-GitHub-Python-Mix-Direct Python target autocomplete suggestions in the format of conversations for OpenAI's fine-tuning. Dataset Details Dataset Description Curated by: [More Information Needed] Funded by [optional]: [More Information Needed] Shared by [optional]: [More Information Needed] Language(s) (NLP): [More Information Needed] License: [More Information Needed] Dataset Sources [optional] The data… See the full description on the dataset page: https://huggingface.co/datasets/23ws-LLMcoder/LLMcoder-GitHub-Python-Mix-Direct.
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1"""This script generates the papers.md file from the papers.yml file."""2from pathlib import Path3 4import yaml5 6data_file = "papers.yml"7papers_header = Path("stylesheets") / "papers_header.txt"8output_file = "papers.md"9 10# Load YAML file:11with open(data_file, "r") as stream:12 papers = yaml.load(stream, Loader=yaml.SafeLoader)["papers"]13 14# Load header:15with open(papers_header, "r") as stream:16 header = stream.read()17 18with open(output_file, "w") as f:19 f.write(header)20 21 # First, we sort the papers by date.22 # This is in the format of "2022-03-15"23 papers = sorted(papers, key=lambda paper: paper["date"], reverse=True)24 25 snippets = []26 for paper in papers:27 title = paper["title"]28 authors = (29 ", ".join(paper["authors"]).replace("(", "<sup>").replace(")", "</sup>")30 )31 affiliations = ", ".join(32 f"<sup>{num}</sup>{affil}" for num, affil in paper["affiliations"].items()33 )34 link = paper["link"]35