LMOps
donut
| LMOps | donut | |
|---|---|---|
| 6 | 19 | |
| 3,186 | 5,312 | |
| 2.7% | 2.0% | |
| 8.1 | 3.6 | |
| 14 days ago | 6 months ago | |
| Python | Python | |
| MIT License | MIT License |
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LMOps
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Has anyone found a way to use Microsoft's Promptist in Stable Diffusion?
Microsoft released an open-sourced prompt optimizer. Has anyone used https://github.com/microsoft/LMOps for prompt optimization? They have it in this demo: https://huggingface.co/spaces/microsoft/Promptist, I'm not sure how to use it for 1.5.
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🚀 Microsoft Open Source LMOps: An AI Prompt Optimization Toolkit For Generative AI Models
Quick Read: https://www.marktechpost.com/2023/02/14/microsoft-open-source-lmops-an-ai-prompt-optimization-toolkit-for-generative-ai-models/ Paper: https://arxiv.org/pdf/2212.09611.pdf Github: https://github.com/microsoft/LMOps
- General technology for enabling AI capabilities with LLMs and Generative models
- microsoft/LMOps: General technology for enabling AI capabilities w/ LLMs and Generative AI models
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Microsoft Promptist : Optimising Stable Diffusion prompts via a language model fine-tuned with reinforcement learning
Project Page : https://github.com/microsoft/LMOps/tree/main/promptist
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?
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
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)
langchain - 🦜🔗 Build context-aware reasoning applications
image-to-sound-python- - A python project for converting an Image into audible sound using OCR and speech synthesis
Awesome-Efficient-LLM - A curated list for Efficient Large Language Models
qlora - QLoRA: Efficient Finetuning of Quantized LLMs
lora-instruct - Finetune Falcon, LLaMA, MPT, and RedPajama on consumer hardware using PEFT LoRA
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"
CUPCAKEAGI - 🧁👋 Welcome to CupcakeAGI, where we bake up some sweet and creamy AGI goodness! 🍰🤖
Multi-Type-TD-TSR - Extracting Tables from Document Images using a Multi-stage Pipeline for Table Detection and Table Structure Recognition:
ImageNet21K - Official Pytorch Implementation of: "ImageNet-21K Pretraining for the Masses"(NeurIPS, 2021) paper
deepdoctection - A Repo For Document AI