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avbiswas/text-albumentations

A simple library for generating instruction tuning datasets locally

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Python
119
22
2 contributors
MIT License
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How fast avbiswas/text-albumentations is gaining stars, and where it lands on Trendshift and GitHub Trending

Activity and trending

Stars, forks and merged pull requests each day or month, lined up with the repository's rank on Trendshift Trending

Sep 5 – Oct 23, 2026

Stars +12 in 49 days

012
2

Forks +2 in 49 days

01
1

Merged PRs 0 in 49 days

01

Trendshift Trendingwhere the repository ranked each day it made the top 25

Not in the Trendshift top 25 in this period

Sep 5Sep 12Sep 19Sep 26Oct 3Oct 10Oct 17
The left and right arrow keys step from day to day; Home and End go to the first and the last

Stars, forks, merged pull requests and Trendshift Trending rank, by day
DayStars gainedForks gainedMerged PRs
Sat, Sep 5, 2026+0+10
Sun, Sep 6, 2026+0+00
Mon, Sep 7, 2026+0+00
Tue, Sep 8, 2026+0+00
Wed, Sep 9, 2026+1+00
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Sat, Sep 19, 2026+0+00
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Tue, Sep 22, 2026+1+00
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Thu, Sep 24, 2026+1+00
Fri, Sep 25, 2026+1+00
Sat, Sep 26, 2026+0+00
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Mon, Sep 28, 2026+0+10
Tue, Sep 29, 2026+2+00
Wed, Sep 30, 2026+1+00
Thu, Oct 1, 2026+0+00
Fri, Oct 2, 2026+0+00
Sat, Oct 3, 2026+0+00
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Wed, Oct 7, 2026+1+00
Thu, Oct 8, 2026+0+00
Fri, Oct 9, 2026+0+00
Sat, Oct 10, 2026+0+00
Sun, Oct 11, 2026+0+00
Mon, Oct 12, 2026+0+00
Tue, Oct 13, 2026+0+00
Wed, Oct 14, 2026+0+00
Thu, Oct 15, 2026+0+00
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Sat, Oct 17, 2026+1+00
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Mon, Oct 19, 2026+0+00
Tue, Oct 20, 2026+0+00
Wed, Oct 21, 2026+0+00
Thu, Oct 22, 2026+0+00
Fri, Oct 23, 2026+0+00
Total+12+20
  • 1#1 on the list
  • 7Rank that day
  • Not trending

Social mentions

Recent discussions about this repository across the web
  1. Sep 211 post
    • My next video is about training JEV from scratch. The first task is to generate SYNTHETIC TRAINING DATA. I already have a library called text-albumentations that uses constrained decoding to generate…

      Read full on X, posted by @neural_avb

      @neural_avb · x.com

  2. 1 month earlier
  3. Aug 201 post
    • Recently trained a tiny 135M LM through - Continued Pretraining (CPT) - Supervised Finetuning (SFT) - Preference Optimization (DPO) - Reinforcement Learning (GRPO) Training data gen, Unsloth, HF,…

      Read full on X, posted by @neural_avb

      @neural_avb · x.com

  4. 2 months earlier
  5. Jun 181 post
    • Btw Joel is the author of the great huggingface article on the Synthetic Data Playbook. It's a marathon survey everyone should read. This is the work that ultimately inspired my text-albumentations…

      Read full on X, posted by @neural_avb

      @neural_avb · x.com

  6. 7 days earlier
  7. Jun 111 post
    • Watch this 35 min visual guide on post-training Tiny Language Models. How to prepare preference datasets, finetune LMs to pick better trajectories, and evaluate their diversity + quality. Training…

      Read full on X, posted by @neural_avb

      @neural_avb · x.com

  8. Jun 61 post2 posts
    • The paper-instructions dataset now comes with a subset of reasoning traces This is an awesome training dataset, curated with deepseek-v4-flash and qwen3.6-35B-A3B using text-albumentations. Costed me…

      Read full on X, posted by @neural_avb

      @neural_avb · x.com

    • Upgrading the paper-instructions dataset 300,000 examples taken from ~3K full text papers and ~10K abstracts... Instruction-out pairs on a bunch of IR tasks: - bullet extraction - qa - rephrasing -…

      Read full on X, posted by @neural_avb

      @neural_avb · x.com

  9. Jun 52 posts
    • Diversity is via the input data and prompts. There's 3000+ full text papers and 20K abstracts, and multiple tasks like qa pairs, summaries, rephrases, KG extracts, counterfactuals, retrieval, etc on…

      Read full on X, posted by @neural_avb

      @neural_avb · x.com

    • So cool that this papers dataset got ~270 downloads last month on HF. It has surpassed ~1000 lifetime. I am working on v2 with more high quality data, as well as more diverse tasks. I will also be…

      Read full on X, posted by @neural_avb

      @neural_avb · x.com

  10. Jun 41 post
    • Btw this is all the code you need to generate high quality instruction/reasoning training data from any-text. Point to a model, input text passage, specify task list (or create custom ones). Done.…

      Read full on X, posted by @neural_avb

      @neural_avb · x.com

  11. 7 days earlier
  12. May 281 post
    • Watch this 45 min video to learn how to create synthetic datasets and train tiny (100M params) local language models that expertise on narrow tasks. Code, datasets, models, harnesses all in comments.

      Read full on X, posted by @neural_avb

      @neural_avb · x.com

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