Results for “nas-bench-nlp”

Process text with NLP. Use when tokenizing, analyzing sentiment, extracting entities, summarizing documents, or measuring similarity.

Use when performing pairwise structural alignments of RNA sequences that incorporate both sequence and structure information through base pair propensity vectors.

Use when extracting structured information from text - named entity recognition, relation extraction, coreference resolution, knowledge graph construction, and information extraction pipelinesUse when ", " mentioned.

NER with Nltk. named entity recognition.

Navigate, manage, and optimize monorepos with tools like Turborepo, Nx, pnpm workspaces, and Lerna. Enables cross-package impact analysis, selective builds and tests, remote caching, dependency graph visualization, and structured multi-repo to monorepo migrations.

Enumerate SMB, WinRM, LDAP, and MSSQL services, validate credentials, spray passwords, and execute commands on remote hosts using NetExec during authorized penetration tests.

NLVR2: A Visual Reasoning Benchmark for Natural Language

Operate and extend NanoClaw v2, a zero-dependency session-aware REPL built on Claude's -p mode.

PyTorch, TensorFlow, neural networks, CNNs, transformers, and deep learning for production

Discover, bet on, track, and settle Hunch prediction markets in natural language with on-chain settlement on Base via x402.

Build and manage monorepos with Nx. Use when a user asks to set up a monorepo, manage multiple packages/apps, cache builds, run affected tests, or migrate from Lerna.

Conduct authenticated and unauthenticated vulnerability scans using Tenable Nessus to identify known vulnerabilities, misconfigurations, and missing patches, with prioritized remediation guidance.

N+1 Query Detection and Resolution

Operate and extend NanoClaw v2, ECC's zero-dependency session-aware REPL built on claude -p.

Builds and trains deep learning models with PyTorch, including tensors, autograd, and neural network modules.