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Announcing jina-ocr-v1, our new visual document parser with 3.4B total parameters and 570M active parameters, with speculative decoding built in. Throw PDFs, scans, tables, charts, or invoices at it and get clean markdown back. Available on 🤗 & Jina Reader `x-respond-with` today

Jina AI

17,851 subscribers

154,660 次观看 • 3 天前 •via X (Twitter)

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Announcing llama-ocr – a free + open source OCR tool! It takes documents (images for now) & outputs markdown, and does really well for complex receipts, PDFs with tables/charts, ect... Powered by Llama 3.2 vision on Together AI & available on npm today!

Announcing llama-ocr – a free + open source OCR tool! It takes documents (images for now) & outputs markdown, and does really well for complex receipts, PDFs with tables/charts, ect... Powered by Llama 3.2 vision on Together AI & available on npm today!

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We're launching 5x faster document parsing in the Firecrawl MCP. Use /parse to turn PDFs, spreadsheets, and docs into LLM-ready data for your agents. Supports running locally or with our hosted MCP server. Try it out today with no API key required on our free tier!

We're launching 5x faster document parsing in the Firecrawl MCP. Use /parse to turn PDFs, spreadsheets, and docs into LLM-ready data for your agents. Supports running locally or with our hosted MCP server. Try it out today with no API key required on our free tier!

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Baidu just open-sourced an OCR model that reads entire 40-page documents in one shot. It's called Unlimited-OCR. 3 billion parameters but only 500 million active during inference. Runs 100% locally on your machine. Why this matters: traditional OCR tools chop documents page by page. Tables that span two pages break. Reading order gets lost. Cross-page context disappears. Unlimited-OCR processes the whole document at once. 32K context window. Text, formulas, tables, reading order all preserved across pages. Output comes out as clean structured Markdown. → 93% accuracy on the standard benchmark. +6 points over the baseline. → Error rate stays below 0.11 even past 40 pages. → Multilingual out of the box. → 2.12 million downloads on Hugging Face last month. 14,600 GitHub stars. For context: Amazon Textract, Google Cloud Vision, and Azure Document Intelligence all charge per page. This runs locally for free.

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Complex workflow? Break it down into sub-workflows for better performance and easier re-use. Now, it’s too easy not to. Steps to get more modular workflows: 1. Select a set of connected nodes 2. Right-click and select Convert to sub-workflow (or Alt + X) 3. Watch magic happen 🪄 🎩 This action will opened a new tab and paste in the selected nodes with their parameters intact! For the encore, the selected nodes in the original workflow will be replaced automagically with a Call My Sub-workflow node. #n8n #lowcode #awesome

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144,429 次观看 • 1 年前

After months of work, and with the help of our awesome community, we're excited to finally share LM Studio 0.3.0! 🎉 🔥 What's new: - Built-in Chat with Documents, 100% offline - OpenAI-like 'Structured Outputs' API with any local model - Total UI revamp (with dark/light/sepia themes) - Load & serve multiple LLMs *on the local network* - Available in 7 languages! 🌎🌍🌏 - Download any supported model from Hugging Face - Update LLM runtimes (llama.cpp) separately from the app ... and tons more goodies! Let us know how you like it! 👾🤝

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LM Studio

142,641 次观看 • 2 年前

If you need McKinsey-style slides, try this prompt: I asked Kimi to conduct a comprehensive analysis of the GenAI video model market, focusing on leading players (e.g., Seedance 2.0, Sora, Kling, Veo, Luma). My prompt: Conduct a comprehensive analysis of the GenAI video model market, focusing on leading players (e.g., Seedance 2.0, Kling, Veo, Luma). Compare their core architectures, temporal consistency, and prompt adherence to identify current industry benchmarks. Use the latest information Requirement: A professional, high-density consulting presentation slide, designed in the style of a top-tier strategy firm (McKinsey/BCG) blended with high-end editorial aesthetics. Core Content & Layout: 1. Rich Data Visualization: The slide is populated with complex, precise charts (stacked bar charts, waterfall charts, or line graphs) and detailed data tables with rows and columns. 2. Structured Frameworks: Includes strategic diagrams or 2x2 matrices constructed with thin, clean lines. 3. High Information Density: The layout is sophisticated and multi-column, mimicking an actual business analysis deck, not just an empty cover page. Visual Style: 1. Aesthetic: Tech-minimalist but information-heavy. Clean, sharp, and authoritative. 2. Typography: Serif fonts (like Times New Roman) for the main headlines to give a premium financial report feel; clean Sans-serif for chart labels and data numbers. 3. Color Palette: Clean white background. Text is sharp black. Charts and graphical accents use Deep Royal Blue and distinct shades of grey for data hierarchy. 4. Graphics: Use fine hairline borders for tables and precise vector lines for graphs.

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Crystal

707,951 次观看 • 7 个月前

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Robinhood

24,543 次观看 • 1 年前

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Inkling-small is out today! With SGLang, you can get 648 tok/s decode with DSpark (simulated acc len=4) and 288 tok/s w/o DSpark, under the same setup (8x NVIDIA AI B200, TP 8, NVFP4, bs=1). What makes this model different is the size. 276B total with 12B active is a sweet spot for RL, and both LoRA and full-parameter training become well within reach. Miles is ready and verified for multimodal RL on Inkling-small, so you can turn your multimodal data into real capability gains. At ~1/4 the size, Inkling-small matches the bigger version in capability and even wins on some benchmarks. Run Inkling-small with SGLang, and customize it with Miles.

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120,134 次观看 • 1 个月前

I am delighted to announce our partnership with Geco.one ! Starting today, DragonX tokens will be available as collateral for leverage trading with our new partner. Geco One ( Is an established, fully regulated European exchange with over 60,000 registered users. Today marks a first step in our partnership. I am excited to continue to work with their team to push Geco One and DragonX forward in adopting new ecosystems. As part of this partnership, the Geco One team was generous enough to facilitate a BitGo listing for DragonX. This is a big step forward, it opens up new opportunities for DragonX to be listed and partner with other regulated institutions. Give a shot today, you can use BTC/ETH/XRP/GECO/DRAGONX as collateral on leverage, going as much as 100x long or short. Geco One supports dozens of the most popular pairs. check them out today.

I am delighted to announce our partnership with Geco.one ! Starting today, DragonX tokens will be available as collateral for leverage trading with our new partner. Geco One ( Is an established, fully regulated European exchange with over 60,000 registered users. Today marks a first step in our partnership. I am excited to continue to work with their team to push Geco One and DragonX forward in adopting new ecosystems. As part of this partnership, the Geco One team was generous enough to facilitate a BitGo listing for DragonX. This is a big step forward, it opens up new opportunities for DragonX to be listed and partner with other regulated institutions. Give a shot today, you can use BTC/ETH/XRP/GECO/DRAGONX as collateral on leverage, going as much as 100x long or short. Geco One supports dozens of the most popular pairs. check them out today.

Erik

12,097 次观看 • 1 年前

The human brain is truly a marvel of nature. If you horribly reductive, and boiled it down to a language model, you'd be looking at roughly 100 trillon parameters running as a sparse MoE architecture Only about 1-5% of neurons fire at any given moment, meaning the brain "activates" maybe 1-5 trillion parameters per inference step. For context, the largest AI models we've built probably top out around 5 trillion parameters. The brain is roughly 100x larger. Even its active params at any given moment are larger than almost every model in existence today. Here's what melts my brain (pun intnended) though Your brain does all of this on about 20 watts of power, less than a dim light bulb. Training a frontier AI model consumes enough electricity to power small cities for months. Running inference across data centers pulls megawatts. Your brain runs 24/7 for 80+ years on the equivalent of a phone charger. We haven't come close to matching the brain's scale. And we're not even in the same universe when it comes to efficiency. Evolution spent 500 million yrs optimizing the most energy-efficient intelligence architecture ever known. we're trying to brute force our way there with compute and electricity. Nature is still the best engineer in the room.

The human brain is truly a marvel of nature. If you horribly reductive, and boiled it down to a language model, you'd be looking at roughly 100 trillon parameters running as a sparse MoE architecture Only about 1-5% of neurons fire at any given moment, meaning the brain "activates" maybe 1-5 trillion parameters per inference step. For context, the largest AI models we've built probably top out around 5 trillion parameters. The brain is roughly 100x larger. Even its active params at any given moment are larger than almost every model in existence today. Here's what melts my brain (pun intnended) though Your brain does all of this on about 20 watts of power, less than a dim light bulb. Training a frontier AI model consumes enough electricity to power small cities for months. Running inference across data centers pulls megawatts. Your brain runs 24/7 for 80+ years on the equivalent of a phone charger. We haven't come close to matching the brain's scale. And we're not even in the same universe when it comes to efficiency. Evolution spent 500 million yrs optimizing the most energy-efficient intelligence architecture ever known. we're trying to brute force our way there with compute and electricity. Nature is still the best engineer in the room.

am.will

130,883 次观看 • 5 个月前

Introducing Extend UI — open-source components for document agents - 14 components & examples for PDF, DOCX, and XLSX viewers, plus bounding box citations, file upload, e-signature, and more - fully customizable - MIT licensed when we started, we tried every file viewer and document component library we could find unfortunately, none of them had all the functionality (and polish) that we wanted, so we ended up building our own for Extend it was only ever meant to be internal, but enough customers kept asking for it that we decided to give it back to the community it's useful for building agents, user-facing document flows, or internal tools we use and maintain it for Extend ourselves, so it'll keep getting better over time (and it's battle tested on millions of pages running through our system every day) it also works with design system agents like Magic Patterns for faster exploration and prototyping available today on the shadcn component registry! some examples in 🧵

Introducing Extend UI — open-source components for document agents - 14 components & examples for PDF, DOCX, and XLSX viewers, plus bounding box citations, file upload, e-signature, and more - fully customizable - MIT licensed when we started, we tried every file viewer and document component library we could find unfortunately, none of them had all the functionality (and polish) that we wanted, so we ended up building our own for Extend it was only ever meant to be internal, but enough customers kept asking for it that we decided to give it back to the community it's useful for building agents, user-facing document flows, or internal tools we use and maintain it for Extend ourselves, so it'll keep getting better over time (and it's battle tested on millions of pages running through our system every day) it also works with design system agents like Magic Patterns for faster exploration and prototyping available today on the shadcn component registry! some examples in 🧵

Kushal Byatnal

171,158 次观看 • 3 个月前

A simple solution to keep our streets clean ♻️ Instead of bottles and cans ending up in the wrong place, you now can leave them on these new bin surrounds, making it easy anyone to pick them up, recycle, and get the deposit back. I’ve seen these bin surrounds working well across Europe so pitched the idea to Dublin City Council and worked closely with the North Inner City task force and council officials to make it happen. Let's get these in Dún Laoghaire next!

A simple solution to keep our streets clean ♻️ Instead of bottles and cans ending up in the wrong place, you now can leave them on these new bin surrounds, making it easy anyone to pick them up, recycle, and get the deposit back. I’ve seen these bin surrounds working well across Europe so pitched the idea to Dublin City Council and worked closely with the North Inner City task force and council officials to make it happen. Let's get these in Dún Laoghaire next!

Ossian Smyth

254,049 次观看 • 1 年前