On IProgrammer: cutt.ly/xr4u6ZQs
#llm #gpt #chatgpt
"Allycat - chat with your website with LLMs"
In this hands-on workshop, I will show how to crawl a website, index data and query it using natural language (not just keywords) with LLMs.
qconsf.com/training/no...
@qconferences.com #QConSF #docling
"Allycat - chat with your website with LLMs"
In this hands-on workshop, I will show how to crawl a website, index data and query it using natural language (not just keywords) with LLMs.
qconsf.com/training/no...
@qconferences.com #QConSF #docling
towardsdatascience.com/docling-the-...
towardsdatascience.com/docling-the-...
a tiny VLM that fits into the docling toolchain that converts PDF->html/markdown painlessly
this addition is now the default for docling
huggingface.co/collections/...
a tiny VLM that fits into the docling toolchain that converts PDF->html/markdown painlessly
this addition is now the default for docling
huggingface.co/collections/...
With the release of RHEL AI 1.3, we’re excited to introduce context aware chunking powered by the Docling project #instructlab
https://www.redhat.com/en/blog/rhel-13-docling-context-aware-chunking-what-you-need-know
Red Hat Blog -
With the release of RHEL AI 1.3, we’re excited to introduce context aware chunking powered by the Docling project #instructlab
https://www.redhat.com/en/blog/rhel-13-docling-context-aware-chunking-what-you-need-know
Red Hat Blog -
huggingface.co/ds4sd/SmolDo...
huggingface.co/ds4sd/SmolDo...
Thanks to @couchbase.bsky.social
Thanks to @couchbase.bsky.social
Try it out yourself, directly from Claude Desktop or via the MCP server or Python SDK.
→ github.com/docling-proj...
Try it out yourself, directly from Claude Desktop or via the MCP server or Python SDK.
→ github.com/docling-proj...
https://link.webring.in.th/2595
https://link.webring.in.th/2595
(1) <a href="https://researchtrend.ai/papers/2501.17887" class="hover:underline text-blue-600 dark:text-sky-400 no-card-link" target="_blank" rel="noopener" data-link="bsky">Docling: An Efficient Open-Source Toolkit for AI-driven Document Conversion
(2) Docling: An Efficient Open-Source Toolkit for AI-driven Document Conversion
🔍 More at researchtrend.ai/communities/LMTD
(1) <a href="https://researchtrend.ai/papers/2501.17887" class="hover:underline text-blue-600 dark:text-sky-400 no-card-link" target="_blank" rel="noopener" data-link="bsky">Docling: An Efficient Open-Source Toolkit for AI-driven Document Conversion
(2) Docling: An Efficient Open-Source Toolkit for AI-driven Document Conversion
🔍 More at researchtrend.ai/communities/LMTD
Whether you're crawling the web (Crawl4AI, FireCrawl) or parsing PDFs (LlamaParse, Docling), raw data access is non-negotiable. No context means no quality answers.
Whether you're crawling the web (Crawl4AI, FireCrawl) or parsing PDFs (LlamaParse, Docling), raw data access is non-negotiable. No context means no quality answers.
Intelligent Document Processing with Python
Register Now: t.ly/FRlwZ
Learn how to automate PDF extraction & OCR using PyMuPDF & Docling — the same AI tools used in real-world data pipelines!
Trainer: Mr. Satish Gupta
Starting From: 1st November | 11:15 AM
#AIWorkshop
Intelligent Document Processing with Python
Register Now: t.ly/FRlwZ
Learn how to automate PDF extraction & OCR using PyMuPDF & Docling — the same AI tools used in real-world data pipelines!
Trainer: Mr. Satish Gupta
Starting From: 1st November | 11:15 AM
#AIWorkshop
ds4sd/SmolDocling-256M-preview
SmolDocling-256M-previewは、効率的なドキュメント変換のために設計されたマルチモーダルな画像テキストtoテキストモデルです。
DoclingDocumentsとの互換性を保ちつつ、Doclingの機能を維持します。
Transformer、vllm、onnxでの推論をサポートします。
ds4sd/SmolDocling-256M-preview
SmolDocling-256M-previewは、効率的なドキュメント変換のために設計されたマルチモーダルな画像テキストtoテキストモデルです。
DoclingDocumentsとの互換性を保ちつつ、Doclingの機能を維持します。
Transformer、vllm、onnxでの推論をサポートします。
ds4sd/SmolDocling-256M-preview
SmolDocling-256M-previewは、効率的なドキュメント変換を目的とした、マルチモーダルな画像-テキストtoテキストモデルです。
Doclingの機能を維持しつつ、DoclingDocumentsとの互換性を確保します。
transformers等を用いて推論可能です。
ds4sd/SmolDocling-256M-preview
SmolDocling-256M-previewは、効率的なドキュメント変換を目的とした、マルチモーダルな画像-テキストtoテキストモデルです。
Doclingの機能を維持しつつ、DoclingDocumentsとの互換性を確保します。
transformers等を用いて推論可能です。
#HackerNews
<a href="https://github.com/feast-dev/feast/tree/master/examples/rag-docling" class="hover:underline text-blue-600 dark:text-sky-400 no-card-link" target="_blank" rel="noopener" data-link="bsky">https://github.com/feast-dev/feast/tree/master/examples/rag-docling
#HackerNews
<a href="https://github.com/feast-dev/feast/tree/master/examples/rag-docling" class="hover:underline text-blue-600 dark:text-sky-400 no-card-link" target="_blank" rel="noopener" data-link="bsky">https://github.com/feast-dev/feast/tree/master/examples/rag-docling
https://github.com/chancat87/docling/pull/100
Result Details
https://github.com/chancat87/docling/pull/100
Result Details