“Model inference”

Create a reduced (fewer-layer) version of a large HuggingFace model for fast testing and debugging.

Team initialization flow (Phase 1 proposal + Phase 2 creation)

WPP semantic-model wrapper over Fabric semantic-model-authoring.

Set up AI Runway on AKS — from bare cluster to running model.

Find Earth2Studio models, data sources, and examples for a weather/climate use case.

Run trained YOLO inference on image folders, save visualized predictions, and export trained weights (ONNX by default) for deployment.

TensorFlow 2.x / Keras patterns and solutions: model building, training loops, classification, regression, NLP, inference serving, Databricks deep learning.

State-space model with O(n) complexity vs Transformers' O(n²).

Use when the model produces a persuasive reasoning narrative that blurs the boundary between observed facts, inferred conclusions, assumptions, tool results…

Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize…

Use ColossalAI for distributed PyTorch training, large-model parallelism, Booster plugins, ShardFormer, Colossal-Inference, and first-party application…

Optimize inference latency, throughput, and cost in production.

Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency.

Plans the stack, database schema and API for an app clone, from the recon map replica-recon wrote.

Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss.

GGUF format and llama.cpp quantization for efficient CPU/GPU inference.

Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching.

Computer vision engineering for object detection, segmentation, and visual AI, covering CNN and Vision Transformer architectures and ONNX/TensorRT deployment.

Generate AI videos using ByteDance Seedance models via Volcengine Ark API.

Build phylogenetic trees end-to-end from raw sequences — MAFFT multiple sequence alignment, optional TrimAl trimming, IQ-TREE 3 maximum-likelihood inference…

Build and run production workloads on Amazon Bedrock with current model availability, Converse API, agents, guardrails, AgentCore, and IAM controls.

Troubleshoots and debugs AWS Clean Rooms collaboration issues related to IAM roles, S3 bucket policies, KMS keys, Lake Formation permissions, and CloudWatch…

Use when writing Python code for DSGE models, HANK models, numerical economic computation, causal inference, or quantitative economic data analysis

Autonomously optimizes end-to-end LLM inference throughput on AMD Instinct GPUs and reports a validated gain, using the Hyperloom multi-agent optimizer.