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catid
supercharger
Python2023–2023
catid / supercharger

supercharger

Supercharge Open-Source AI Models

2Distinct people
2Mentions
0Explicit recommenders
347GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Supercharge Open-Source AI Models

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, 5:04:57 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: 2023-04-16 00:56:17 UTC to 2023-07-11 14:12:14 UTC. Weeks start Monday, UTC.

012023-04-10 00:00:00 UTC to 2023-04-17 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsApr 102023-04-17 00:00:00 UTC to 2023-04-24 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-04-24 00:00:00 UTC to 2023-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-05-01 00:00:00 UTC to 2023-05-08 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-05-08 00:00:00 UTC to 2023-05-15 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-05-15 00:00:00 UTC to 2023-05-22 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-05-22 00:00:00 UTC to 2023-05-29 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsMay 222023-05-29 00:00:00 UTC to 2023-06-05 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-06-05 00:00:00 UTC to 2023-06-12 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-06-12 00:00:00 UTC to 2023-06-19 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-06-19 00:00:00 UTC to 2023-06-26 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-06-26 00:00:00 UTC to 2023-07-03 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-07-03 00:00:00 UTC to 2023-07-10 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-07-10 00:00:00 UTC to 2023-07-17 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJul 10

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
Apr 102023-04-10 00:00:00 UTC2023-04-17 00:00:00 UTC110
Apr 172023-04-17 00:00:00 UTC2023-04-24 00:00:00 UTC000
Apr 242023-04-24 00:00:00 UTC2023-05-01 00:00:00 UTC000
May 12023-05-01 00:00:00 UTC2023-05-08 00:00:00 UTC000
May 82023-05-08 00:00:00 UTC2023-05-15 00:00:00 UTC000
May 152023-05-15 00:00:00 UTC2023-05-22 00:00:00 UTC000
May 222023-05-22 00:00:00 UTC2023-05-29 00:00:00 UTC000
May 292023-05-29 00:00:00 UTC2023-06-05 00:00:00 UTC000
Jun 52023-06-05 00:00:00 UTC2023-06-12 00:00:00 UTC000
Jun 122023-06-12 00:00:00 UTC2023-06-19 00:00:00 UTC000
Jun 192023-06-19 00:00:00 UTC2023-06-26 00:00:00 UTC000
Jun 262023-06-26 00:00:00 UTC2023-07-03 00:00:00 UTC000
Jul 32023-07-03 00:00:00 UTC2023-07-10 00:00:00 UTC000
Jul 102023-07-10 00:00:00 UTC2023-07-17 00:00:00 UTC101

What Hacker News says

2 sources
Since I've been on a AI code-helper kick recently. According to the post, Claude 2 now 71.2%, a significant upgrade from 1.3 (56.0%). (Found in model card: pass@1) For comparison: * GPT-4 claims 85.4 on HumanEval, in a recent paper https://arxiv.org/pdf/2303.11366.pdf GPT-4 was tested at 80.1 pass@1 and 91 pass@1 using their Reflexion technique. They also include MBPP and Leetcode Hard benchmark comparisons * WizardCoder, a StarCoder fine-tune is one of the top open models, scoring a 57.3 pass@1, model card here: https://huggingface.co/WizardLM/WizardCoder-15B-V1.0 * The best open model I know of atm is replit-code-instruct-glaive, a replit-code-3b fine tune, which scores a 63.5% pass@1. An independent developer abacaj has reproduced that announcement as part of code-eval, a repo for getting human-eval results: https://github.com/abacaj/c
Read the rest
ode-eval Those interested in this area may also want to take a look at this repo https://github.com/my-other-github-account/llm-humaneval-ben... that also ranks with Eval+, the CanAiCode Leaderboard https://huggingface.co/spaces/mike-ravkine/can-ai-code-resul... and airate https://github.com/catid/supercharger/tree/main/airate Also, as with all LLM evals, to be taken with a grain of salt... Liu, Jiawei, Chunqiu Steven Xia, Yuyao Wang, and Lingming Zhang. “Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation.” arXiv, June 12, 2023. https://doi.org/10.48550/arXiv.2305.01210.
In Claude 2

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