Step-by-step guide to building a resume skill extraction pipeline using Mistral-7B running on a DigitalOcean GPU Droplet. The tutorial covers setting up a GPU Droplet, installing vLLM to serve Mistral-7B as an OpenAI-compatible API, configuring DigitalOcean Spaces for PDF storage, and writing a Python script that downloads resume PDFs, extracts text with PyMuPDF, sends it to the inference endpoint, and exports structured candidate data (skills, roles, companies, experience) to Excel and JSON files uploaded back to Spaces.
Table of contents
IntroductionKey TakeawaysPrerequisitesStep 1 – Creating a DigitalOcean GPU DropletStep 2 – Installing Python and creating a virtual environmentStep 3 – Installing Project DependenciesStep 4 – Installing vLLM for GPU InferenceStep 5 – Starting the Mistral-7B Inference ServerStep 6 – Verifying the Inference EndpointStep 7 – Configuring DigitalOcean Spaces for Resume StorageStep 8 – Creating the Environment Configuration FileStep 9 – Writing the Resume Processing ScriptStep 10 – Running the Resume Extraction PipelineStep 11 – Viewing the Extracted Resume DataFAQConclusionFuture scopeResourcesSort: