Search Results for "markdown windows"

DeepSeek-OCR-2 is the second-generation optical character recognition system developed to improve document understanding by introducing a “visual causal flow” mechanism, enabling the encoder to reorder visual tokens in a way that better reflects semantic structure rather than strict raster scan order. It is designed to handle complex layouts and noisy documents by giving the model causal reasoning capabilities that mimic human visual scanning behavior, enhancing OCR performance on documents...

DSH Better Sidebar is a plugin that turns the DeepSeek Harness interface into a fuller development workspace. It adds a file explorer, code editor, previews, an embedded browser, real terminal sessions, Git tools, and background-task views. Tabs can be moved, split, and shared between the right sidebar and bottom panel. File previews cover code, images, Markdown, HTML, PDF, Word, Excel, and PowerPoint content. Session-specific layouts and tabs persist locally, while mobile layouts collapse...

ChatGPT Clone demonstrates a ChatGPT-style conversational interface wired to large-language-model backends, packaged so developers can self-host and extend. The goal is to replicate the core chat UX—message history, streaming tokens, code blocks, and system prompts—while letting you plug in different provider APIs or local models. It showcases a clean separation between the web client and the message orchestration layer so you can experiment with prompts, roles, and memory strategies. The...

NuMarkdown-8B-Thinking is the first reasoning OCR vision-language model (VLM) designed to convert documents into clean Markdown optimized for retrieval-augmented generation (RAG). Built on Qwen 2.5-VL-7B and fine-tuned with synthetic Doc → Reasoning → Markdown examples, it generates thinking tokens before producing the final Markdown to better handle complex layouts and tables. It uses a two-phase training process: supervised fine-tuning (SFT) followed by reinforcement learning (GRPO) with a...

Gemopus is a supervised fine-tuned version of the Gemma 4 26B instruction model, designed with a “stability first” philosophy that prioritizes reliable reasoning structure over aggressive chain-of-thought imitation. Instead of relying on distilled reasoning traces from external models, it focuses on preserving Gemma’s native reasoning style while improving answer clarity, structure, and consistency. The model enhances response organization through better use of formatting, improves...