Maxxroot

321 posts

Maxxroot

Maxxroot

@maxxroot

Katılım Mart 2020
280 Takip Edilen67 Takipçiler
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Erick
Erick@ErickSky·
TENCENT ACABA DE DROPEAR LA BOMBA para todos los que hacen AI Agents: Un sandbox que: - Arranca en menos de 60 ms (hasta 50x más rápido) - Usa solo 5 MB de RAM por instancia - Puedes correr +2.000 sandboxes en un solo servidor - Seguridad de verdad (microVMs con KVM + RustVMM) - y 100% compatible con E2B SDK. Self-hosted, open-source y GRATIS. REPOOO👇
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bearstech
bearstech@bearstech·
Plane : un outil de gestion de projet Open Source conçu comme une alternative moderne à Jira, Linear ou ClickUp. 👉 github.com/makeplane/plane
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bearstech
bearstech@bearstech·
Un bon retour d'expérience sur la migration de Cloudflare vers bunny.net, une alternative européenne prometteuse. (L) 👉 jola.dev/posts/dropping…
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bearstech
bearstech@bearstech·
Twenty : un CRM Open Source conçu pour offrir une alternative moderne, flexible et économique aux solutions propriétaires comme Salesforce. 👉 Le projet : github.com/twentyhq/twenty 👉 En savoir plus : twenty.com
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chiefofautism
chiefofautism@chiefofautism·
shannon is a claude code but for hacking (pentesting)
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GitHub Projects Community
GitHub Projects Community@GithubProjects·
Verify email addresses without sending a single email
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Akshay 🚀
Akshay 🚀@akshay_pachaar·
Fine-tune DeepSeek-OCR on your own language! (100% local) DeepSeek-OCR is a 3B-parameter vision model that achieves 97% precision while using 10× fewer vision tokens than text-based LLMs. It handles tables, papers, and handwriting without killing your GPU or budget. Why it matters: Most vision models treat documents as massive sequences of tokens, making long-context processing expensive and slow. DeepSeek-OCR uses context optical compression to convert 2D layouts into vision tokens, enabling efficient processing of complex documents. The best part? You can easily fine-tune it for your specific use case on a single GPU. I used Unsloth to run this experiment on Persian text and saw an 88.26% improvement in character error rate. ↳ Base model: 149% character error rate (CER) ↳ Fine-tuned model: 60% CER (57% more accurate) ↳ Training time: 60 steps on a single GPU Persian was just the test case. You can swap in your own dataset for any language, document type, or specific domain you're working with. I've shared the complete guide in the next tweet - all the code, notebooks, and environment setup ready to run with a single click. Everything is 100% open-source!
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Tom Dörr
Tom Dörr@tom_doerr·
A terminal user interface for managing ufw firewall rules
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Sumanth
Sumanth@Sumanth_077·
Turn PDF files into clean, LLM-ready data! Doctly turns unstructured documents into structured, machine-readable data. Upload PDFs, invoices, contracts, reports and turn them into perfectly formatted Markdown or JSON in seconds. Key Features: • AI accuracy – unmatched accuracy for document conversion and data extraction. • Fast & scalable – process thousands of documents in parallel. • Simple – one REST endpoint, or a fully-typed Python SDK. • Secure – encrypted in transit & at rest, built with best-practice security controls. Get LLM-ready data from any document with just a few lines of code.
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Tom Dörr
Tom Dörr@tom_doerr·
Scans a network and generates an interactive topology visualization
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bearstech
bearstech@bearstech·
Checkov : un scanner Open Source d'infrastructure as code pour détecter les vulnérabilités et les mauvaises configurations. "Policy-as-code for everyone" 👉 le projet : github.com/bridgecrewio/c… 👉 En savoir plus : checkov.io
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bearstech
bearstech@bearstech·
EverShop : une solution e‑commerce Open Source API-first construite autour de Node.js, React et GraphQL. 👉 le projet : github.com/evershopcommer…
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