Results for “lean”

Minimal silhouette artwork of [subject, e.g. a giraffe and acacia tree / a couple on a hill] against a vivid gradient sunset sky from [color] to [color]. Pure black silhouettes, a large glowing sun, a few birds, clean and graphic, great as wall art. --ar 3:2

An intricate perfectly symmetrical mandala with [number] layers of [motifs, e.g. lotus petals, paisleys and tiny dots], centered on a [color or white] background. [Choose: clean black line art for coloring / rich jewel-tone colors with gold accents]. Crisp fine lines, high detail, radial symmetry, print-ready.

A friendly cartoon avatar of [description: age, hair, glasses, clothing, vibe], head-and-shoulders, smiling, facing slightly to the side. Clean vector style, soft shading, solid [color] circular background, suitable as a social media profile picture.

An isometric miniature of a [type of place, e.g. busy Tokyo street corner] on a floating square tile: shops with tiny signs, trees, cars, people, street lights. Clean 3D render, soft shadows, pastel palette, tilt-shift feel, plain [color] background. --ar 1:1

Abstract composition of smooth glossy 3D shapes [e.g. twisted torus, spheres and ribbons] floating in space, iridescent [colors, e.g. purple to orange] gradients, soft studio lighting, subtle reflections, clean minimal background. Premium tech-brand aesthetic. --ar 16:9

Character turnaround reference sheet of [character description, e.g. a young desert courier with a scarf, goggles and a big satchel], showing front view, 3/4 view, side view and back view standing in a neutral pose on a plain light-grey background. Consistent proportions and outfit details across all views, clean line…

Glowing neon line art of [subject, e.g. a tiger head] drawn with continuous single-weight tubes of light in [two colors, e.g. hot pink and electric cyan] on a deep black brick wall. Soft bloom and light spill on the wall, subtle reflections, crisp clean curves, no other details. --ar 4:5

You are a machine learning engineer. Problem: [classification / regression] Data: [columns, target, size] Goal: [what decision the model supports] Write a scikit-learn pipeline: data loading, cleaning, feature engineering, train/test split, a baseline model and a stronger model, cross-validation, appropriate metrics,…

Suggest better names in this code. Language and naming conventions: [details] ``` [paste] ``` For each unclear name, give 2–3 alternatives and explain why they're clearer. Then show the code with the best names applied. Don't change behaviour.

Act as a senior iOS developer. iOS target: [version] Screen: [purpose and elements] Data: [model and source] Navigation: [details] Write a SwiftUI view with a view model (ObservableObject or @Observable), loading/error/empty states, accessibility labels, Dynamic Type support, previews, and comments.

Act as a senior software architect. Project type: [web app, API, mobile app, library] Stack: [details] Team size and expected growth: [details] Features: [list] Propose a folder structure (with explanation of each folder), layering (e.g. routes, services, data access), naming conventions, where tests live, configurati…

Write a [Python / Node.js] script to transform data. Input format and sample: [paste] Desired output format and sample: [paste] Rules: [renames, filters, calculations, date formats] The script should read from a file, handle missing or malformed values, log problems, write the output file, and be easy to rerun. Includ…