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microsoft
CodeBERT
Python2024–2024
microsoft / CodeBERT

CodeBERT

CodeBERT

2Distinct people
2Mentions
0Explicit recommenders
2.8KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

CodeBERT

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 6:01:08 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by week2 dated mentions

Observed mentions: 2024-09-19 15:46:18 UTC to 2024-11-25 10:13:56 UTC. Weeks start Monday, UTC.

012024-09-16 00:00:00 UTC to 2024-09-23 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsSep 162024-09-23 00:00:00 UTC to 2024-09-30 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-09-30 00:00:00 UTC to 2024-10-07 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-07 00:00:00 UTC to 2024-10-14 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-14 00:00:00 UTC to 2024-10-21 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-21 00:00:00 UTC to 2024-10-28 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsOct 212024-10-28 00:00:00 UTC to 2024-11-04 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-11-04 00:00:00 UTC to 2024-11-11 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-11-11 00:00:00 UTC to 2024-11-18 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-11-18 00:00:00 UTC to 2024-11-25 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-11-25 00:00:00 UTC to 2024-12-02 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsNov 25

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Sep 162024-09-16 00:00:00 UTC2024-09-23 00:00:00 UTC101
Sep 232024-09-23 00:00:00 UTC2024-09-30 00:00:00 UTC000
Sep 302024-09-30 00:00:00 UTC2024-10-07 00:00:00 UTC000
Oct 72024-10-07 00:00:00 UTC2024-10-14 00:00:00 UTC000
Oct 142024-10-14 00:00:00 UTC2024-10-21 00:00:00 UTC000
Oct 212024-10-21 00:00:00 UTC2024-10-28 00:00:00 UTC000
Oct 282024-10-28 00:00:00 UTC2024-11-04 00:00:00 UTC000
Nov 42024-11-04 00:00:00 UTC2024-11-11 00:00:00 UTC000
Nov 112024-11-11 00:00:00 UTC2024-11-18 00:00:00 UTC000
Nov 182024-11-18 00:00:00 UTC2024-11-25 00:00:00 UTC000
Nov 252024-11-25 00:00:00 UTC2024-12-02 00:00:00 UTC101

What Hacker News says

1 sources
Stumbled on this piece while searching for Code Review on Google. > Microsoft Research and LinkedIn researchers have open-sourced CodeReviewer, a pre-trained transformer model that can automatically assess code changes, generate review comments, and suggest fixes. Trained on 7.9M pull requests across 9 programming languages, it achieves a 71.5% F1 score in identifying problematic code changes and can generate relevant review comments with 3.6/5.0 informativeness rating from human evaluators. > Unlike existing code models, CodeReviewer is specifically trained on code diffs and real-world review comments from high-quality GitHub repositories. The model outperforms previous approaches by learning to "think" like a code reviewer rather than just understanding source code. Technical details and model available at: https://github.com/microsoft/
Read the rest
CodeBERT/tree/master/CodeReview... I'm thinking GitHub is gonna use some of this learning in Copilot?
In Automating Code Reviews Using Large Language Models

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