You will get the AI Agent Skills Framework for Hugging Face Model Training & Evaluation
Project details
I provide a structured Hugging Face automation setup for model training, evaluation, and workflow standardization. This project focuses on creating reusable Python-based pipelines that simplify dataset management, training configuration, and validation processes.
The solution is designed to work smoothly with Hugging Face Hub and modern AI tooling environments. I will configure a clean training script, evaluation workflow, and structured project setup so you can easily reproduce, extend, or automate future model experiments.
You will receive well-organized source code, clear documentation, and a modular structure that supports scalable experimentation. My goal is to deliver a reliable and maintainable ML workflow — not just a script, but a reusable system.
The solution is designed to work smoothly with Hugging Face Hub and modern AI tooling environments. I will configure a clean training script, evaluation workflow, and structured project setup so you can easily reproduce, extend, or automate future model experiments.
You will receive well-organized source code, clear documentation, and a modular structure that supports scalable experimentation. My goal is to deliver a reliable and maintainable ML workflow — not just a script, but a reusable system.
Machine Learning Tools
Amazon SageMaker, ChatGPT, GitHub Copilot, GPT-3, Kubeflow, MLflow, NumPy, pandas, Python, PyTorch, scikit-learn, Sonnet, Vertex AIWhat's included
| Service Tiers |
Starter
$250
|
Standard
$600
|
Advanced
$1,200
|
|---|---|---|---|
| Delivery Time | 5 days | 8 days | 17 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 1 | 3 | 5 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code |
Frequently asked questions
About Novanob
AI-Native Next.js Developer | Claude API Specialist | Career Clarity
Gondomar, Portugal - 2:44 pm local time
I help founders launch transformational platforms that guide users from career confusion, job loss, or major transitions to clarity, purpose, and inspired next steps — exactly like your Wayfind project.
I have deep, hands-on experience fixing the exact pain points you described: Claude JSON parsing failures, blank/missing fields, encoding issues, incomplete renders, and unreliable AI results. I deliver polished, trustworthy Next.js frontends where the AI always works and the user experience feels real and human.
Live AI-powered platforms I personally built and shipped:
tryapt.ai → AI career assessment + archetype clarity platform with reliable structured outputs
ikigaitool → Guided Ikigai self-discovery flow with clean AI results and emotional progression
perfectday.ai → Immersive “Perfect Day” visualization and daily alignment experience (directly matches your core module)
What I bring to your Wayfind MVP
Expert-level Claude API integration with strict JSON schema validation (Zod) + automatic retry + graceful fallbacks
Production-grade Next.js (App Router), TypeScript, Tailwind CSS, Vercel deployments
Focus on emotional UX and transformational flows (no infinite spinners, no blank results, no garbled text)
Product-builder mindset: I stabilize first, then polish the homepage, lead capture, coach CTAs, and revenue flows
Fast, clear communication and 2–3 hour paid test availability to prove results immediately
Tech I use daily for projects like yours:
Next.js • React • TypeScript • Claude API • Structured JSON outputs • Vercel • Tailwind CSS • Resend • Zod validation
I’m available more than 30 hrs/week, communicate fluently in English, and ready to move quickly on your 1–2 week MVP launch.
Let’s turn your prototype into a launch-ready, trustworthy career clarity platform that users love and trust.
Steps for completing your project
After purchasing the project, send requirements so Novanob can start the project.
Delivery time starts when Novanob receives requirements from you.
Novanob works on your project following the steps below.
Revisions may occur after the delivery date.
Project Analysis & Setup
Review requirements, confirm model type, and define workflow structure.
Training Pipeline Configuration
Configure Hugging Face training script, datasets, and evaluation settings.