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Life & fun · alternatives · 2026

24 alternatives to Using LLama2 to Correct OCR Errors

I've been disappointed by the very poor quality of results that I generally get when trying to run OCR on older scanned documents, especially ones that are typewritten or otherwise have unusual or irregular typography. I recently had the idea of using Llama2 to use common sense reasoning and subject level expertise to correct transcription errors in a "smart" way-- basically doing what a human proofreader who is familiar with the topic might do. I came up with the linked script that takes a PDF as input, runs Tesseract on it to get an initial text extraction, and then feeds this…

This tool improves OCR accuracy on older scanned documents by combining Tesseract OCR with Llama2 AI. The script extracts text from PDFs, then uses Llama2 to correct transcription errors and format output as markdown… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Using LLama2 to Correct OCR Errors launched in 2023; newer entries below may have overtaken it.

  1. 1

    Almost exactly 1 year ago, I submitted something to HN about using Llama2 (which had just come out) to improve the output of Tesseract OCR by correcting obvious OCR errors [0]. That was exciting at the time because OpenAI's API calls were still quite expensive for GPT4, and the cost of running it on a book-length PDF would just be prohibitive. In contrast, you could run Llama2 locally on a machine with just a CPU, and it would be extremely slow, but "free" if you had a spare machine lying around. Well, it's amazing how things have changed since then. Not only have models gotten a lot better,…

    2024 · github.com · its alternatives →

  2. 2

    Pure Javascript OCR for more than 100 Languages 📖🎉🖥 - naptha/tesseract.js

    2016 · github.com · its alternatives →

  3. 3

    I've developed a Python API service that uses GPT-4o for OCR on PDFs. It features parallel processing and batch handling for improved performance. Not only does it convert PDF to markdown, but it also describes the images within the PDF using captions like `[Image: This picture shows 4 people waving]`. In testing with NASA's Apollo 17 flight documents, it successfully converted complex, multi-oriented pages into well-structured Markdown. The project is open-source and available on GitHub. Feedback is welcome.

    2024 · github.com · its alternatives →

  4. 4

    Last week was big for open source LLMs. We got: - Qwen 2.5 VL (72b and 32b) - Gemma-3 (27b) - DeepSeek-v3-0324 And a couple weeks ago we got the new mistral-ocr model. We updated our OCR benchmark to include the new models. We evaluated 1,000 documents for JSON extraction accuracy. Major takeaways: - Qwen 2.5 VL (72b and 32b) are by far the most impressive. Both landed right around 75% accuracy (equivalent to GPT-4o’s performance). Qwen 72b was only 0.4% above 32b. Within the margin of error. - Both Qwen models passed mistral-ocr (72.2%), which is specifically trained for OCR. - Gemma-3…

    2025 · github.com · its alternatives →

  5. 5
    Llama 2▲263

    The next generation of Meta's open source LLM

    2023 · developer.meta.com · its alternatives →

  6. 6

    🔍 Better text detection by combining multiple OCR engines (EasyOCR, Tesseract, and Pororo) with 🧠 LLM. - junhoyeo/BetterOCR

    2023 · github.com · its alternatives →

  7. 7

    I recently submitted another project for using LLMs to correct errors and improve formatting of OCRed documents which was well received. The low cost and high quality/speed of the latest "value tier" models from OpenAI and Anthropic have made it possible to get compelling results at a very reasonable price in that application. It occured to me that the same approach taken there (namely, splitting documents into chunks and sending each chunk through a chain of LLM prompts that each take the output of the previous prompt and apply an additional layer of processing) could be easily applied…

    2024 · github.com · its alternatives →

  8. 8

    I've been playing around with https://github.com/zphang/minimal-llama/ and https://github.com/tloen/alpaca-lora/blob/main/finetune.py, and wanted to create a simple UI where you can just paste text, tweak the parameters, and finetune the model quickly using a modern GPU. To prepare the data, simply separate your text with two blank lines. There's an inference tab, so you can test how the tuned model behaves. This is my first foray into the world of LLM finetuning, Python, Torch, Transformers, LoRA, PEFT, and Gradio. Enjoy!

    2023 · github.com · its alternatives →

  9. 9

    We believe that AI should be fully open source and part of the collective knowledge. The original LLaMA code is GPL licensed which means any project using it must also be released under GPL. This "taints" any other code and prevents meaningful academic and commercial use. Lit-LLaMA solves that for good.

    2023 · github.com · its alternatives →

  10. 10

    I built OCR Arena as a free playground for the community to compare leading foundation VLMs and open-source OCR models side-by-side. Upload any doc, measure accuracy, and (optionally) vote for the models on a public leaderboard. It currently has Gemini 3, dots.ocr, DeepSeek, GPT5, olmOCR 2, Qwen, and a few others. If there's any others you'd like included, let me know!

    Nov 2025 · ocrarena.ai · its alternatives →

  11. 11

    A Python wrapper for the tesseract-ocr API. Contribute to sirfz/tesserocr development by creating an account on GitHub.

    2016 · github.com · its alternatives →

  12. 12
    OCR Wiz▲119

    Accurately extract text from images (including handwriting)

    2024 · apps.apple.com · its alternatives →

  13. 13

    📄 PDF/IMG ->.MD/JSON Document OCR API for PaddleOCR and GLMOCR. Self-hostable. - majcheradam/ocrbase

    Jan 2026 · github.com · its alternatives →

  14. 14

    Turn hundreds of documents into one clean spreadsheet

    Feb 2026 · nolainocr.com · its alternatives →

  15. 15

    Hi HN, I’ve been working on an OCR pipeline specifically optimized for machine learning dataset preparation. It’s designed to process complex academic materials — including math formulas, tables, figures, and multilingual text — and output clean, structured formats like JSON and Markdown. Some features: • Multi-stage OCR combining DocLayout-YOLO, Google Vision, MathPix, and Gemini Pro Vision • Extracts and understands diagrams, tables, LaTeX-style math, and multilingual text (Japanese/Korean/English) • Highly tuned for ML training pipelines, including dataset generation and…

    2025 · github.com · its alternatives →

  16. 16

    Author here. I just wanted a quick and easy way to easily submit strings to a REST API and get back the embedding vectors in JSON using Llama2 and other similar LLMs, so I put this together over the past couple days. It's very quick and easy to set up and totally self-contained and self-hosted. You can easily add new models to it by simply adding the HuggingFace URL to the GGML format model weights. Two models are included by default, and these are automatically downloaded the first time it's run. It lets you not only submit text strings and get back the embeddings, but also to compare two…

    2023 · github.com · its alternatives →

  17. 17

    OCR/Document extraction field has seen lot of action recently with releases like Mixtral OCR, Andrew Ng's agentic document processing etc. Also there are several benchmarks for OCR, however all testing for something slightly different which make good comparison of models very hard. To give an example, some models like mixtral-ocr only try to convert a document to markdown format. You have to use another LLM on top of it to get the final result. Some VLM’s directly give structured information like key fields from documents like invoices, but you have to either add business rules on top…

    2025 · nanonets.com · its alternatives →

  18. 18
    PDF2MD▲51

    Convert your PDFs to markdown With AI OCR

    2024 · its alternatives →

  19. 19

    Design tailored document processing APIs, deploy in minutes

    2024 · mindee.com · its alternatives →

  20. 20BV

    Vision models have been gaining popularity as a replacement for traditional OCR. Especially with Gemini 2.0 becoming cost competitive with the cloud platforms. We've been continuously evaluating different models since we released the Zerox package last year (https://github.com/getomni-ai/zerox). And we wanted to put some numbers behind it. So we’re open sourcing our internal OCR benchmark + evaluation datasets. Full writeup + data explorer here: https://getomni.ai/ocr-benchmark Github: https://github.com/getomni-ai/benchmark Huggingface:…

    2025 · getomni.ai · its alternatives →

  21. 21

    Hi HackerNews, Lately, I have seen an explosion in posts offering paid APIs/services to get unstructured data into LLMs (i.e. langchain extract, ragflow, unstructured, unstract, just to name a few) and I have been largely disappointed by them, either because they fail to implement multimodal support, fail to give good context for "really tricky" PDFs / Word docs / Powerpoints, or are just plain difficult to use. In light of all these posts I figured I'd share my solution that has been working smoothly for me and my clients. I put it up on GitHub for free so you can check it…

    2024 · github.com · its alternatives →

  22. 22

    We've been building data pipelines that scrape websites and extract structured data for a while now. If you've done this, you know the drill: you write CSS selectors, the site changes its layout, everything breaks at 2am, and you spend your morning rewriting parsers. LLMs seemed like the obvious fix — just throw the HTML at GPT and ask for JSON. Except in practice, it's more painful than that: - Raw HTML is full of nav bars, footers, and tracking junk that eats your token budget. A typical product page is 80% noise. - LLMs return malformed JSON more often than you'd expect, especially with…

    Mar 2026 · github.com · its alternatives →

  23. 23OO

    Built this because people working with large document sets had no free tool that handled batch processing cleanly. Tesseract is free and runs locally. For anything that needs more accuracy — Google Vision, Gemini, or any OpenRouter model — you bring your own API key. No subscription, no markup on your usage. Export as TXT, JSON, XML or PDF. AI engines support custom prompts so you can translate, extract form fields, or get structured output in one step. App: https://onlineocrfree.qzz.io Source: https://github.com/naimurhasan/online-ocr-free

    Mar 2026 · onlineocrfree.qzz.io · its alternatives →

  24. 24

    I've been tinkering with getting Llama-8B to bootstrap its own research skills through self-play. The model generates questions about documents, searches for answers, and then learns from its own successes/failures through RL (hacked up Unsloth's GRPO code). Started with just 23% accuracy on Apollo 13 mission report questions and hit 53% after less than an hour of training. Everything runs locally using open-source models. It's cool to see the model go from completely botching search queries to iteratively researching to get the right answer.

    2025 · github.com · its alternatives →

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