'nsf' 검색 결과

Turn a travel idea or draft itinerary into a practical plan by researching routes, entry requirements, transfers, costs, and daily timing. Compare meaningful alternatives, track unresolved choices, and coordinate live availability checks through a separate booking workflow.

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• Compare destinations, dates, and routes
• Build a realistic multi-day itinerary
• Check entry requirements and airport transfers

Implement caching and data conversion for syncable entities in Twenty's server code. Build lookup maps, convert stored records and inputs into flat representations, and resolve references to universal identifiers for later validation and processing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a cache service for a new syncable entity
• Convert stored entities into flat data
• Transform creation and update inputs

Inspect and transform local DICOM medical imaging files, including metadata, image frames, and compression formats. Generate technical inventories and preview images, check installed codecs, and review pseudonymized derivatives without treating those checks as proof of de-identification.

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• Create a technical inventory of local DICOM files
• Check compression support and frame memory needs
• Export a frame as a non-diagnostic preview

Optimize scientific Python workloads for NVIDIA GPUs by choosing suitable libraries and reducing bottlenecks. Compare outputs with the CPU version and measure complete processing time, including data transfers, to determine whether the GPU implementation provides a useful improvement.

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• Assess whether slow Python processing would benefit from a GPU
• Move NumPy or pandas workloads to suitable GPU libraries
• Validate GPU results against CPU outputs

Organize research sources in self-hosted Open Notebook, then search them, ask questions with citations, create notes, transform text, or generate podcasts with multiple speakers. Supports REST API automation and configuration of local or cloud AI providers.

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• Collect PDFs and web sources in a research notebook
• Ask questions about selected sources with citations
• Apply custom summaries and text transformations

Plan and document studies that assess whether an analytical procedure suits its intended use. Select the governing framework, evaluate calibration, accuracy, precision, and detection limits, and compare methods using acceptance criteria defined before data collection.

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• Planning analytical validation studies and acceptance criteria
• Evaluating calibration, accuracy, and precision
• Estimating and confirming detection and quantitation limits

Build and operate genomics workloads on DNAnexus using its command-line tools and Python SDK. The skill covers data transfers, app configuration checks, workflow imports, execution monitoring, and explicit cost controls for reproducible analysis workflows.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Transfer and organize genomics data on DNAnexus
• Validate app configuration and build applets
• Import WDL, CWL, or Nextflow workflows

Compare how proxies and backend servers interpret HTTP requests in a CTF sandbox. Use paired requests and logs to pinpoint differences in paths, headers, or message boundaries, then document a minimal reproduction of unintended routing.

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• Compare HTTP interpretation across proxies and backend servers
• Investigate path normalization and decoding differences
• Trace routing changes caused by ambiguous headers

Analyze packet captures in a CTF sandbox by rebuilding communication sessions and decoding message contents. Recover transferred files and connect packet order, timing, and reconstructed streams to observed host or malware behavior.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Rebuild TCP or UDP communication sessions
• Decode HTTP, DNS, or custom protocol messages
• Recover files transferred over the network

Helps plan and implement database structure changes and data transformations using Sequelize, TypeORM, or Prisma. Includes staged changes intended to avoid downtime, plus transaction and backup examples for rolling back failed migrations.

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• Renaming database columns in stages
• Splitting stored addresses into separate fields
• Preparing rollback steps for failed migrations

Prepare handoffs between engineers responsible for responding to system incidents. Organize active incidents, investigations, recent changes, and upcoming events into shift summaries, with guidance for mid-incident transfers, asynchronous updates, and checks that the incoming engineer receives alerts.

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• Prepare an on-call shift handoff summary
• Transfer incident response leadership during an active incident
• Arrange asynchronous handoffs across time zones

Design dbt data transformations with clearly organized models, data quality tests, documentation, and incremental processing that updates only part of a dataset. Use it to structure analytics tables and organize a dbt project.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Organizing a dbt project into model layers
• Adding data quality tests
• Designing incremental updates for large tables

Investigate suspected data theft from AWS S3 by comparing access logs, GuardDuty findings, and Macie classifications. Identify unusual bulk downloads and transfers across accounts, assess sensitive data exposure, and build automated detection rules.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating unusual bulk downloads from S3
• Checking transfers to external AWS accounts
• Assessing exposure of sensitive data

Prepare for a career change by identifying skills that apply across industries and rewriting experience in language suited to a target role. Develop resume structure, identify skill gaps, and draft a clear explanation for the transition.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Identifying skills useful in another industry
• Rewriting work experience for a target role
• Planning ways to fill skill gaps

Use Outlines to make language models produce data in a defined format. The skill covers extracting information into JSON, restricting classification labels, and applying Pydantic models, which define fields and data types, with local model backends.

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• Extracting company or profile details into JSON
• Classifying text using a fixed set of labels
• Generating text that matches a specified pattern

Guide language model training with TRL, from learning to follow instructions to matching human preferences. Covers method selection, training data, reward models that score responses, evaluation, and adjustments for memory limits or unstable training.

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• Train a model on instruction and response examples
• Align responses using preferred and rejected answer pairs
• Build a training pipeline using human feedback

Reduce the memory needed to run large language models with GPTQ quantization, which stores model weights at lower precision. Covers loading compressed models, quantizing your own models, choosing execution backends, and connecting to memory-efficient fine-tuning.

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• Run a language model within limited GPU memory
• Load a pre-quantized model for text generation
• Quantize and save your own trained model

Extend the amount of text a language model can process at once. Compares RoPE, YaRN, ALiBi, and position interpolation, with implementation examples, additional training guidance, and memory optimization approaches for long document processing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Extend an existing model to handle longer inputs
• Compare methods for representing token positions
• Plan additional training with long documents

Helps configure and troubleshoot DeepSpeed for training large models across multiple devices. Covers memory optimization, parallel training, and DeepNVMe storage transfers, with examples for tuning data movement and configuring models that divide work among specialized components.

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• Configuring distributed training for large models
• Tuning tensor transfers to NVMe storage
• Setting up models with specialized expert components

Train smaller language models using knowledge distillation, where a larger model supplies examples or prediction targets. This skill covers training losses, generated training data, parameter choices, and output comparisons to support model compression and specialized student models.

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• Training a smaller model from a larger teacher
• Fine-tuning with teacher-generated responses
• Distilling domain knowledge into a specialized model

Analyze single-cell data with scvi-tools, using deep learning to combine datasets, correct differences between experiments, and transfer cell labels. Model guides and reusable scripts cover RNA, protein, chromatin accessibility, spatial data, and downstream analysis.

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• Integrate single-cell RNA datasets and correct batch effects
• Analyze paired RNA and protein or RNA and ATAC measurements
• Transfer cell-type labels from reference data

Extract fields, filter records, and reshape JSON from API responses, configuration files, or logs using Crush’s built-in jq. Get help writing and debugging transformations, constructing new JSON, and formatting output for other commands.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Extract selected fields from API responses
• Filter JSON arrays by conditions
• Reshape configuration data or construct JSON

Write JavaScript for n8n Code nodes to aggregate, filter, and transform workflow data. Guidance covers data access, output formats, execution modes, common errors, and performance choices when processing large numbers of records.

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• Aggregating and deduplicating multiple records
• Transforming complex API responses
• Fixing data access and return format errors

Build n8n workflows that download, transform, and send files without losing their contents. Learn how file data differs from JSON, how to preserve attachments, and how to use storage keys or URLs with AI tools and chat messages.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Fixing attachments lost during data transformation
• Passing uploaded files to AI agent tools
• Displaying generated images in chat