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encord-team
encord-active
Python2023–2024
encord-team / encord-active · Archived

encord-active

The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.

2Distinct people
4Mentions
0Explicit recommenders
461GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

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Also in these discussions

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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 month4 dated mentions

Observed mentions: 2023-05-09 16:32:13 UTC to 2024-01-31 18:14:11 UTC.

012023-05-01 00:00:00 UTC to 2023-06-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsMay 20232023-06-01 00:00:00 UTC to 2023-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-07-01 00:00:00 UTC to 2023-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-08-01 00:00:00 UTC to 2023-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-09-01 00:00:00 UTC to 2023-10-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsSep 20232023-10-01 00:00:00 UTC to 2023-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-11-01 00:00:00 UTC to 2023-12-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2023-12-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2024-02-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJan 2024

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
May 20232023-05-01 00:00:00 UTC2023-06-01 00:00:00 UTC110
Jun 20232023-06-01 00:00:00 UTC2023-07-01 00:00:00 UTC000
Jul 20232023-07-01 00:00:00 UTC2023-08-01 00:00:00 UTC000
Aug 20232023-08-01 00:00:00 UTC2023-09-01 00:00:00 UTC000
Sep 20232023-09-01 00:00:00 UTC2023-10-01 00:00:00 UTC101
Oct 20232023-10-01 00:00:00 UTC2023-11-01 00:00:00 UTC000
Nov 20232023-11-01 00:00:00 UTC2023-12-01 00:00:00 UTC110
Dec 20232023-12-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
Jan 20242024-01-01 00:00:00 UTC2024-02-01 00:00:00 UTC101

What Hacker News says

4 sources
Webinar from last week on how to fine-tune VFMs, specifically Meta's Segment Anything Model (SAM). What you'll need to follow along the fine-tuning walkthrough: Images, ground-truth masks, and optionally, prompts from the Stamp Verification (StaVer) Dataset on Kaggle (https://www.kaggle.com/datasets/rtatman/stamp-verification-s...) Download the model weights for SAM the official GitHub repo (https://github.com/facebookresearch/segment-anything) Good understanding of the model architecture Segment Anything paper (https://ai.meta.com/research/publications/segment-anything/) GPU infra the NVIDIA A100 should do for this fine-tuning. Data curation and model evaluation tool Encord Active (https://github.com/encord-team/encord-active) Colab walkthrough for fine-tuning: https://colab.research.google.com/github/encord-team/encord-... I'd love
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to get your thoughts and feedback. Thank you.
In How to Fine-Tune Foundation Models to Auto-Label Training Data

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