DB-GPT
donut
| DB-GPT | donut | |
|---|---|---|
| 10 | 19 | |
| 11,055 | 5,312 | |
| 5.0% | 2.9% | |
| 9.9 | 3.6 | |
| 4 days ago | 6 months ago | |
| Python | Python | |
| MIT License | MIT License |
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DB-GPT
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(2/2) May 2023
Interact your data and environment using the local GPT (https://github.com/csunny/DB-GPT)
- FLaNK Stack Weekly 29 may 2023
- GitHub - csunny/DB-GPT: Interact your data and environment using the local GPT, no data leaks, 100% privately, 100% security
- DB-GPT - OSS to interact with your local LLM
- Show HN: DB-GPT, an LLM tool for database
donut
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Ask HN: Why are all OCR outputs so raw?
maybe this is better? https://github.com/clovaai/donut
I'm not sure
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Show HN: BetterOCR combines and corrects multiple OCR engines with an LLM
Yup! But I'm still exploring options. (any recommendations would be welcomed!) Here are some candidates I'm considering:
- https://github.com/mindee/doctr
- https://github.com/open-mmlab/mmocr
- https://github.com/PaddlePaddle/PaddleOCR (honestly I don't know Mandarin so I'm a bit stuck)
- https://github.com/clovaai/donut - While it's primarily an "OCR-free document understanding transformer," I think it's worth experimenting with. Think I can sort this out by letting the LLM reason through it multiple times (although this will impact performance)
- yesterday got a suggestion to consider https://github.com/kakaobrain/pororo - I don't think development is still active but the results are pretty great on Korean text
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New to ML, looking for some GPU and learning material info
I am also interested in experimenting with something like DONUT (https://github.com/clovaai/donut) but I have never seen anything on what the VRAM expectations are for something like this. Does anyone know also if there are any newer better models than this for document parsing as well? Or what the VRAM requirements for something like this tend to be?
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[D] Is there a good ai model for image-to-text where the images are diagrams and screenshots of interfaces?
Here are a few useful resources you could start with: [Pix2Struct by Google Research](https://github.com/google-research/pix2struct) might be a valuable tool, although it will most likely need some fine-tuning to fit your specifics. You can also find some fine-tuned models on HuggingFace by searching 'pix2struct'. Another option worth considering is [DonutI](https://github.com/clovaai/donut). Like Pix2Struct, fine-tuning likely needed to meet your requirements. Tesseract OCR is another alternative, particularly for handling text. It's primarily designed for pages of text, think books, but with some tweaking and specific flags, it can process tables as well as text chunks in regions of a screenshot. Bit too much tweaking for my taste. As I'm also in search of OCR tools for UI and chart screenshots, so share if you find something else.
- How to Automate Document Extraction from Insurance Documents
- FLaNK Stack Weekly 29 may 2023
- Donut: OCR-Free Document Understanding Transformer
What are some alternatives?
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
PaddleOCR - Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)
GPTCache - Semantic cache for LLMs. Fully integrated with LangChain and llama_index.
image-to-sound-python- - A python project for converting an Image into audible sound using OCR and speech synthesis
gorilla - Gorilla: An API store for LLMs
qlora - QLoRA: Efficient Finetuning of Quantized LLMs
zamm - Experimental AI chat app
CascadeTabNet - This repository contains the code and implementation details of the CascadeTabNet paper "CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents"
Propan - Propan is a powerful and easy-to-use Python framework for building event-driven applications that interact with any MQ Broker
Multi-Type-TD-TSR - Extracting Tables from Document Images using a Multi-stage Pipeline for Table Detection and Table Structure Recognition:
jj - JSON Stream Editor (command line utility)
deepdoctection - A Repo For Document AI