Transformer Explainer is an interactive visualization tool designed to help anyone learn how Transformer-based models like GPT work. It runs a live GPT-2 model right in your browser, allowing you to experiment with your own text and observe in real time how internal components and operations of the Transformer work together to predict the next tokens. Try Transformer Explainer at http://poloclub.github.io/transformer-explainer
If you prompt for a 360ยฐ video in VEO (like literally write “360ยฐ” ) it can generate a Monoscopic 360 video, then the next step is to inject the right metadata in your file so you can play it as an actual 360 video. Once it’s saved with the right Metadata, it will be recognized as an actual 360/VR video, meaning you can just play it in VLC and drag your mouse to look around.
There are three models, two are available now, and a third open-weight version is coming soon:
FLUX.1 Kontext [pro]: State-of-the-art performance for image editing. High-quality outputs, great prompt following, and consistent results.
FLUX.1 Kontext [max]: A premium model that brings maximum performance, improved prompt adherence, and high-quality typography generation without compromise on speed.
Coming soon: FLUX.1 Kontext [dev]: An open-weight, guidance-distilled version of Kontext.
Weโre so excited with what Kontext can do, weโve created aย collection of modelsย on Replicate to give you ideas:
theย 8 most important model typesย and what theyโre actually built to do: โฌ๏ธ
1. ๐๐๐ โ ๐๐ฎ๐ฟ๐ด๐ฒ ๐๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ ๐ ๐ผ๐ฑ๐ฒ๐น โ Your ChatGPT-style model. Handles text, predicts the next token, and powers 90% of GenAI hype. ๐ Use case: content, code, convos.
2. ๐๐๐ โ ๐๐ฎ๐๐ฒ๐ป๐ ๐๐ผ๐ป๐๐ถ๐๐๐ฒ๐ป๐ฐ๐ ๐ ๐ผ๐ฑ๐ฒ๐น โ Lightweight, diffusion-style models. Fast, quantized, and efficient โ perfect for real-time or edge deployment. ๐ Use case: image generation, optimized inference.
3. ๐๐๐ โ ๐๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ ๐๐ฐ๐๐ถ๐ผ๐ป ๐ ๐ผ๐ฑ๐ฒ๐น โ Where LLM meets planning. Adds memory, task breakdown, and intent recognition. ๐ Use case: AI agents, tool use, step-by-step execution.
4. ๐ ๐ผ๐ โ ๐ ๐ถ๐ ๐๐๐ฟ๐ฒ ๐ผ๐ณ ๐๐ ๐ฝ๐ฒ๐ฟ๐๐ โ One model, many minds. Routes input to the right โexpertโ model slice โ dynamic, scalable, efficient. ๐ Use case: high-performance model serving at low compute cost.
5. ๐ฉ๐๐ โ ๐ฉ๐ถ๐๐ถ๐ผ๐ป ๐๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ ๐ ๐ผ๐ฑ๐ฒ๐น โ Multimodal beast. Combines image + text understanding via shared embeddings. ๐ Use case: Gemini, GPT-4o, search, robotics, assistive tech.
6. ๐ฆ๐๐ โ ๐ฆ๐บ๐ฎ๐น๐น ๐๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ ๐ ๐ผ๐ฑ๐ฒ๐น โ Tiny but mighty. Designed for edge use, fast inference, low latency, efficient memory. ๐ Use case: on-device AI, chatbots, privacy-first GenAI.
7. ๐ ๐๐ โ ๐ ๐ฎ๐๐ธ๐ฒ๐ฑ ๐๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ ๐ ๐ผ๐ฑ๐ฒ๐น โ The OG foundation model. Predicts masked tokens using bidirectional context. ๐ Use case: search, classification, embeddings, pretraining.
8. ๐ฆ๐๐ โ ๐ฆ๐ฒ๐ด๐บ๐ฒ๐ป๐ ๐๐ป๐๐๐ต๐ถ๐ป๐ด ๐ ๐ผ๐ฑ๐ฒ๐น โ Vision model for pixel-level understanding. Highlights, segments, and understands *everything* in an image. ๐ Use case: medical imaging, AR, robotics, visual agents.
Tencent just made Hunyuan3D 2.1 open-source. This is the first fully open-source, production-ready PBR 3D generative model with cinema-grade quality. https://github.com/Tencent-Hunyuan/Hunyuan3D-2.1
What makes it special? โข Advanced PBR material synthesis brings realistic materials like leather, bronze, and more to life with stunning light interactions. โข Complete access to model weights, training/inference code, data pipelines. โข Optimized to run on accessible hardware. โข Built for real-world applications with professional-grade output quality.
They’re making it accessible to everyone: โข Complete open-source ecosystem with full documentation. โข Ready-to-use model weights and training infrastructure. โข Live demo available for instant testing. โข Comprehensive GitHub repository with implementation details.
