Plugins

1 plugin

Results for “re-embedding”

15 skills
More results
github
Qdrant Search Quality Diagnosis
Diagnoses Qdrant search quality issues by isolating causes like HNSW approximation, quantization, embedding model, or search pipeline problems.
36.2k
adobe
Reskin
Rebuild existing site pages with byte-faithful content on a separately-defined donor design system, preserving text, images, and metadata while applying a new visual design.
142 · bundle
nvidia
Tao Finetune Cosmos Embed
Fine-tune, evaluate, run inference, and export Cosmos-Embed1 video-text embedding models for tasks like text-to-video retrieval and semantic deduplication.
2.2k · bundle
adobe
Replica
Re-platforms a site to AEM Edge Delivery (or any clean front end) while keeping its current design near pixel-perfect. Recreates key pages as clean HTML/CSS, verifies each against the live site with a measured source-fidelity gate, then hands off for site-wide delivery.
142 · bundle
nvidia
Tao Train Reid
Trains, evaluates, exports, and runs inference for person re-identification models using TAO, learning discriminative embeddings for cross-camera matching.
2.2k · bundle
nvidia
Tao Mine Aoi Images
Embeds target and source image parquets, then mines nearest-neighbour source images for augmentation in VCN AOI workflows.
2.2k · bundle
nvidia
Tao Finetune Clip
Fine-tune and deploy CLIP vision-language models for zero-shot classification, image-text retrieval, and embedding extraction with ONNX and TensorRT support.
2.2k · bundle
heygen
Hyperframes Registry
Install, discover, and wire reusable blocks and components into HyperFrames compositions using the CLI.
· bundle
adobe
Geo Rewrite
Rewrites AEM Edge Delivery Services page content for AI search discoverability (Generative Engine Optimization) by analyzing structure, clarity, and factual density.
142 · bundle
elevenlabs
Agents
Build voice AI agents with natural conversations, multiple LLM providers, custom tools, and easy web embedding.
363 · bundle
huggingface
Hf Cloud Sagemaker Deployment Planner
Plans and coordinates the deployment of a model to Amazon SageMaker AI, selecting the appropriate pathway (real-time, serverless, async, batch, or Bedrock CMI) based on model type, traffic, latency, and cost constraints.
10.8k