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Qwen-Image is a text-to-image foundation model with advanced multilingual text rendering.Downloadableqwen-image
Generate synthetic PCB inspection images on Kubernetes with the SMT Defect Image Generation (DIG) DAG in CDF Orchestration. The DAG renders components in simulation, turns the renders into realistic golden images (sim2real), and uses AnomalyGen to add tex Run the CDF Orchestration Image Attribute Augmentation DAG on Kubernetes - person-crop clothing augmentation, attribute search, and augmented dataset generation. Select for requests about image attribute augmentation, person attribute search, person re-id FLUX 3 Image Klein is a state-of-the-art open-weight image generation and editing modelDownloadableflux-3-image-klein
Use to flash a promoted BSP image to a Jetson DUT in RCM mode via flash.sh or l4t_initrd_flash.sh. Do NOT use for BSP customization, image promotion, or carrier derivation. Extract Jetson Linux + sample-rootfs tarballs and run apply_binaries.sh for the active target, then record bsp_image in the profile. Use after jetson-init-target; not for source-tree setup. Use to promote overlay files and built artifacts into the staged BSP image. Do NOT use to flash or build. Triggers: promote bsp image. Use after jetson-flash-image to run static BSP checks, on-target smoke/regression tests on a flashed DUT, or both. Not for build or flash steps. Triggers: validate bsp, on-target validation. Use when the user wants to orchestrate defect image generation with NVIDIA Cosmos AnomalyGen (Cosmos-Predict2-derived) on OSMO for PCBA, metal surface, and glass inspection. The Day 0 path handles cold-start with USD-to-ROI, image-edit augmentation, and A Qwen-Image-Edit is an image editing model with multilingual text editing and strong subject consistency.Downloadableqwen-image-edit
An image edit model specialized for Omniverse synthetic to photographic solder-light style captured at NVIDIA PCB inspection stationsDownloadableqwen-image-edit-nvpcb-ovsl2sl
Run TAO Data Services image embedding to turn a parquet of image filepaths into an embedding parquet using CLIP, SigLIP, or a TAO checkpoint. Use when a workflow needs embeddings before nearest-neighbor or unique-neighbor mining, or when the user asks to Two-step image grounding pipeline: extracts referring expressions from (image, caption) pairs and grounds them to pixel-space bounding boxes via a VLM. Use when the user wants to ground captions to bboxes, generate phrase-grounded annotations, auto-label Runs the DEFT embed-then-mine workflow for VCN AOI iterations — embeds the gap-analysis target parquet, embeds a source pool, and mines nearest-neighbour source images for downstream augmentation. Use as the immediate next step after `tao-route-visual-cha Run TAO Data Services TMM unique-neighbor matching mining from embedding parquet files for object detection workflows. Use when an object detection workflow needs to mine a bijectively-assigned set of unique source images closest to target samples. Use gl PyTorch-based TAO image classification. Supports a wide range of backbones (FAN, EfficientNet, ResNet, etc.) with distillation and quantization for deployment. Use when training, evaluating, distilling, quantizing, exporting, or running inference for a TA Train a concept LoRA on FLUX.2 Klein with AI ToolkitIntermediate4 HOURSFine-Tune FLUX.2 Klein for Custom Image Generation
FLUX.2 image and LTX-2 video workflows you run locally with full creative controlIntermediate13 MINGenerate Images and Video with ComfyUI
Node-based diffusion workflows for images and videos with FLUX, Wan, HunyuanVideo, and Stable DiffusionIntermediate2 HOURSGenerate Images and Videos with ComfyUI
MiniMax-M3.1-Flash is a native multimodal mixture-of-experts model for coding, agentic workflows, computer use, and cybersecurity.Free Endpointminimax-m3.1-flash
Mistral Large 4 from Mistral AI, a 1T-total / 52B-active granular MoE for text and image input with reasoning, function calling and structured outputs, served in NVFP4 with DSpark speculative decoding.Free EndpointMistral Large 4
Preview of StepFun's Step 5: ~600B-total / 27B-active multimodal MoE (text and image in, text out) with 1M context, reasoning and tool calling, served in NVFP4.Free EndpointStep 5 Preview
Generate exponentially large amounts of synthetic motion trajectories for robot manipulation from just a few human demonstrations.RoboticsEnterpriseSynthetic Manipulation Motion Generation for Robotics
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