---
title: Texttoimage
emoji: 🖼
colorFrom: purple
colorTo: red
sdk: gradio
sdk_version: 5.25.2
app_file: app.py
pinned: false
license: mit
---
Skills Used to built this app:


🎨 AI/ML & Diffusion Model Skills

Understanding diffusion models – how Stable Diffusion works.

Using Hugging Face diffusers – loading and running pretrained pipelines.

GPU/CPU optimization – switching between cuda and cpu, choosing float16 vs float32.

Prompt engineering – crafting effective prompts for image generation.

Negative prompting – removing unwanted artifacts from images.

Random seed control – reproducibility in image generation.

Model parameter tuning – adjusting guidance_scale, num_inference_steps.

Memory optimization – handling large models (SDXL Turbo ~6GB).

🌐 Web App & UI Skills

Gradio UI design – creating blocks, rows, sliders, and image outputs.

Event handling in Gradio – binding run button, prompt submit, and examples.

Custom styling (CSS) – controlling layout (#col-container).

User experience (UX) design – hiding advanced settings but making them available.

Interactive demos – gr.Examples, progress tracking.

Frontend/backend linking – connecting UI inputs to model inference.

☁️ Deployment & DevOps Skills

Hugging Face Spaces deployment – running apps in free/shared GPU environments.

ZeroGPU understanding – optional GPU resource management.

Creating requirements.txt – ensuring dependencies install correctly.

Cloud CI/CD basics – automatic app rebuilds when pushing to repo.

Containerization awareness – understanding how HF Spaces run your app in a container.

📊 Software Engineering Practices

Testing & validation – making sure inference works across devices.

Error handling – handling missing CUDA, API errors, busy servers.

Performance benchmarking – checking image generation speed vs settings.

Scalability awareness – how this app could scale from 1 to 1M users.

Documentation & communication – writing clear README, comments, and usage guides.

🧑‍💻 Programming & Software Skills

Using external libraries (pip/requirements) – managing dependencies like torch, diffusers, gradio.

Debugging Python code – fixing errors (e.g., wrong gr.Text vs gr.Textbox).

Version control (Git/GitHub) – managing source code and pushing to repos.

Software architecture design – structuring functions (infer, UI) cleanly.

Object-oriented programming basics – understanding pipelines and classes.


Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference