NodeShift Announcements Official

NodeShift Announcements Official

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Updated: May 13, 2026 at 9:12 AM

NodeShift Announcements Official

Decentralized, no-code AI cloud platform that enables one-click deployment of AI agents and LLMs

@nodeshiftcloud is a growing community focused on oneclick and llms and related topics

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NodeShift Announcements Official

May 26, 2026, 07:34 AM

SoulX-Podcast-1.7B — Long-Form, Multi-Speaker TTS Is Here!

SoulX-Podcast-1.7B is a podcast-style TTS model built for long, multi-turn, multi-speaker dialogs. It supports English, Mandarin, and several Chinese dialects (Sichuanese, Henanese, Cantonese), performs zero-shot voice cloning from short clips, and even captures laughter, sighs, and emotions to make speech sound real.

It’s optimized for single-GPU inference, letting you generate entire podcast episodes with expressive delivery, natural tone, and dynamic speaker changes.

Key Highlights:
✅ Long-form conversational TTS with speaker variation
✅ Zero-shot cloning from short reference clips
✅ Multilingual + multi-dialect support
✅ Runs smoothly on 8–24 GB GPUs for smaller use cases
✅ Perfect for podcasts, storytelling, or research in expressive speech

We just published a new step-by-step guide covering:
✅ Complete NodeShift GPU setup (CUDA 12.1.1 devel image)
✅ Python 3.11 + Conda environment setup
✅ Installing PyTorch (cu121) and all dependencies
✅ Pulling base + dialect models from Hugging Face
✅ Running dialogue inference scripts
✅ Launching the Gradio WebUI for real-time podcast generation

Read the full guide here: https://nodeshift.cloud/blog/how-to-install-run-soulx-podcast-1-7b-locally

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NodeShift Announcements Official

May 26, 2026, 07:34 AM

🎥 Video

OpenAI just released GPT-OSS-Safeguard — a new era of open-source safety reasoning!

OpenAI’s GPT-OSS-Safeguard 20B and 120B models are purpose-built for Trust & Safety, trained to interpret your own policy text, explain moderation decisions, and let you control reasoning effort (low / medium / high).

🔹 20B → optimized for 16 GB-class GPUs, perfect for low-latency filters & offline labeling
🔹 120B → high-fidelity safety reasoning, fits a single H100 80 GB via MoE + MXFP4 quantization
🔹 Fully open-weight under Apache 2.0, built on the GPT-OSS family
🔹 Requires the Harmony response format for interpretable

We’ve just published a step-by-step guide covering everything you need to:
✅ Deploy GPT-OSS-Safeguard Models
✅ Pull & run the models via Ollama CLI
✅ Launch Open WebUI for a visual chat experience
✅ Explore reasoning depth, labeling workflows, and real-world policy checks

Read the full guide here: https://nodeshift.cloud/blog/how-to-install-run-gpt-oss-safeguard-20b-and-120b-locally

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NodeShift Announcements Official

May 26, 2026, 07:34 AM

Meet VieNeu-TTS, the first-ever Vietnamese Text-to-Speech model that runs entirely on your personal device.
Built on the Qwen 0.5B LLM and fine-tuned from NeuTTS Air, it delivers hyper-realistic, natural voices with real-time inference, no heavy hardware dependency.
If you’re building voice assistants, educational tools, or offline AI applications, VieNeu-TTS is a game-changer for anyone who values speed, privacy, and quality.
In this step-by-step guide, we show you how to install and run VieNeu-TTS locally, and experience the future of Vietnamese voice AI right away.
🔗 Read the full article here: https://nodeshift.cloud/blog/how-to-install-run-vieneu-tts-locally-the-first-realistic-vietnamese-voice-ai?utm_source=telegram&utm_medium=social&utm_campaign=vieneu_tts_launch

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NodeShift Announcements Official

May 26, 2026, 07:34 AM

Meet JanusCoderV-8B — the next leap in visual-programmatic intelligence!

Developed by InternLM, JanusCoderV-8B is an 8-billion-parameter multimodal model built on InternVL-3.5-8B, trained on the massive JANUSCODE-800K corpus. It’s designed to unify vision and code, enabling image-conditioned code generation, visually grounded edits, and UI-to-code translation — all in one model.

What makes it special?
✅ It bridges the gap between visual context and programmatic logic.
✅ Generates HTML/CSS, charts, and interactive elements directly from screenshots or design mockups.
✅ Supports long-context outputs (up to 32K tokens) and runs smoothly on affordable GPUs using 8-bit or BF16 precision.

We’ve just published a new step-by-step guide:

How to Install & Run JanusCoderV-8B Locally — a complete walkthrough that covers:
✅ Setting up a GPU-powered VM on NodeShift Cloud
✅ Installing CUDA 12.1.1, Python 3.11, and PyTorch 2.5.1
✅ Configuring the environment for multimodal inference
✅ Running JanusCoderV-8B to generate image-based code and UI descriptions

Read the full guide here: https://nodeshift.cloud/blog/how-to-install-run-januscoderv-8b-locally

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NodeShift Announcements Official

May 26, 2026, 07:34 AM

AMD Releases Nitro-E — A Lightweight Text-to-Image Diffusion Model

AMD has introduced Nitro-E, a highly efficient text-to-image diffusion model built on the E-MMDiT architecture (~304M parameters). It’s designed for fast, low-cost training and inference, making image generation accessible even on modest GPU setups.

Key Highlights:
🔹 Ultra-light architecture (~304M params) with EMMDiT backbone.
🔹 Base 512px model delivers quality in ~20 steps.
🔹 Distilled 512px variant generates great results in just 4 steps.
🔹 GRPO-tuned checkpoint for improved post-training image quality.
🔹 Fully compatible with both NVIDIA (CUDA) and AMD (ROCm) GPUs.

We’ve just published a complete step-by-step guide covering everything you need to install and run AMD Nitro-E locally.

Inside this guide, you’ll learn:
✅ How to set up a GPU VM on NodeShift Cloud.
✅ Environment setup with Python 3.11, CUDA 12.1, and required libraries.
✅ Installation of PyTorch, Diffusers, and FlashAttention.
✅ Running Nitro-E in multiple modes — base, distilled, and GRPO-tuned.
✅ Generating your first AI image in just a few minutes.

Read the full guide here: https://nodeshift.cloud/blog/how-to-install-run-amd-nitro-e-locally

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NodeShift Announcements Official

May 26, 2026, 07:34 AM

Kimi Linear by Moonshot AI is the Future of Scalable Attention!
Imagine handling 1 million tokens with 6× faster decoding and 75% less memory, that’s what Kimi Linear delivers.

Built on the groundbreaking Kimi Delta Attention (KDA), it redefines how we process long-context data with unmatched speed, efficiency, and precision.

In our latest guide, we break down how to install and run Kimi Linear locally so you can experience next-gen attention models firsthand, right from your own setup. If you're into LLM research, RL-style reasoning, or long-context applications, this one’s a must-try.
🔗 Read full detailed article here: https://nodeshift.cloud/blog/a-step-by-step-guide-to-install-run-kimi-linear?utm_source=telegram&utm_medium=social&utm_campaign=kimi_linear_launch

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NodeShift Announcements Official

May 26, 2026, 07:34 AM

Tired of slow, laggy OCR pipelines? LightOnOCR-1B emerges as a fast and lightweight open source OCR model that outpaces many well known OCRs on benchmarks.
With a Pixtral-based Vision Transformer and Qwen3 text decoder, it delivers end-to-end differentiable OCR, no external steps needed.
- 5× faster than dots.ocr
- Processes 493k pages/day for <$0.01 per 1,000 pages
- Handles math, tables, receipts, forms, and multi-column layouts effortlessly
- State-of-the-art accuracy (76.1 overall on Olmo-Bench)

You can now install and run it locally, right on your machine, with the help of the latest step-by-step guide powered by NodeShift Cloud.
🔗 Read the full guide here: https://nodeshift.cloud/blog/how-to-install-and-run-lightonocr-1b-locally-the-fastest-open-ocr-model-for-document-understanding?utm_source=telegram&utm_medium=social&utm_campaign=lightonocr1b_launch

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NodeShift Announcements Official

May 26, 2026, 07:34 AM

Datalab just released their next-generation OCR model — Chandra!

Chandra is a powerful vision-language OCR model built for precise document understanding. It doesn’t just extract text — it reconstructs full document layouts into clean Markdown, HTML, or JSON formats, handling tables, forms, diagrams, handwriting, math equations, and multi-column pages with ease.

Supporting over 40 languages, Chandra achieves an impressive 83.1% overall accuracy on the olmOCR benchmark, outperforming many open and commercial OCR systems.

We’ve just published a comprehensive guide that walks you through everything — from setting up Chandra on a GPU-powered NodeShift Cloud VM, installing dependencies, and running the model with Transformers and vLLM, to launching a full Streamlit web app for interactive document analysis in the browser.

Whether you’re a researcher, developer, or just passionate about document AI, this guide will help you get Chandra running end-to-end — from terminal to web UI.

Check out the full guide here: https://nodeshift.cloud/blog/how-to-install-run-chandra-ocr-locally

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NodeShift Announcements Official

May 26, 2026, 07:34 AM

Baidu's PaddleOCR-VL is the new SOTA vision-language model redefining document understanding and trending as one of the top OCR models along with big models like DeepSeek OCR.
This is a compact yet insanely capable OCR-VLM that blends:
- NaViT-style dynamic visual encoding
- ERNIE-4.5-0.3B language model
- Support for 109 languages
- Lightning-fast, resource-efficient inference

It doesn’t just read documents, it understands and explains them. From complex tables and formulas to multi-lingual text and charts, PaddleOCR-VL achieves state-of-the-art accuracy while staying lightweight enough for real-world deployment.
At NodeShift, we made it even easier to install, run, and benchmark PaddleOCR-VL locally, so you can experience its power without the complex setup friction.
🔗 Read here: https://nodeshift.cloud/blog/how-to-install-and-run-paddleocr-vl-locally?utm_source=telegram&utm_medium=social&utm_campaign=paddleocr-vl-launch

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NodeShift Announcements Official

May 26, 2026, 07:34 AM

Imagine creating minutes-long, high-quality 720p videos, all from text or a single image, right on your own machine.
That’s exactly what LongCat-Video (13.6B parameters) makes possible.

What it offers:
- Unified model for Text-to-Video, Image-to-Video, & Video-Continuation
- Generates smooth, coherent long videos with no color drift or frame drops
- Efficient inference powered by Block Sparse Attention
- Trained with multi-reward RLHF for cinematic realism

With NodeShift Cloud, you can now install, run, and scale LongCat-Video locally or on the cloud in just a few steps, unlocking studio-grade AI video generation for everyone.
🔗 Dive into the full guide here: https://nodeshift.cloud/blog/how-to-install-and-run-longcat-video-locally-generate-stunning-long-videos-with-ai?utm_source=telegram&utm_medium=social&utm_campaign=longcat_video_launch

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