--- language: - en library_name: transformers pipeline_tag: text-generation license: apache-2.0 base_model: - Tesslate/UIGEN-FX-4B-Preview tags: - web-generation - html - css - tailwind-css - ui-generation - web-design - small-model - qwen3 - transformers model-index: - name: UIGEN-FX-4B-Preview results: [] datasets: - Tesslate/UIGEN-T2 ---
FX = “Frontend Engineer.” This upgrade in the UIGEN line focuses on better visual polish, functional structure, and web-ready markup to ship cleaner, more complete websites from a single prompt. This model was trained on A11y, Axe, and Lighthouse scores to improve SEO, Accesibility, and reproducibility for users.
UIGEN-FX-4B-Preview is a 4B parameter UI generation model tuned to behave like a frontend engineer across 22 Frameworks.
Small enough for laptops and fast iteration, while keeping strong structure and visual consistency. FX emphasizes layout rhythm, spacing, and component composition to reduce cleanup work.
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
model_id = "Tesslate/UIGEN-FX-4B-Preview"
tok = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16,
device_map="auto"
)
prompt = """Make a single-file landing page for 'LatticeDB'.
Style: modern, generous whitespace, Tailwind, rounded-xl, soft gradients.
Sections: navbar, hero (headline + 2 CTAs), features grid, pricing (3 tiers),
FAQ accordion, footer. Constraints: semantic HTML, no external JS."""
inputs = tok(prompt, return_tensors="pt").to(model.device)
out = model.generate(**inputs, max_new_tokens=2200, temperature=0.6, top_p=0.9)
print(tok.decode(out[0], skip_special_tokens=True))
vllm serve Tesslate/UIGEN-FX-4B-Preview \ --host 0.0.0.0 --port 8000 \ --max-model-len 65536 \ --gpu-memory-utilization 0.92
python -m sglang.launch_server \ --model-path Tesslate/UIGEN-FX-4B-Preview \ --host 0.0.0.0 --port 5000 \ --mem-fraction-static 0.94 \ --attention-backend flashinfer \ --served-model-name UIGEN-FX-4B-Preview
Tip: Lower temperature (0.4–0.6) yields stricter, cleaner markup; raise it for more visual variety.
| Param | Value | Notes |
|---|---|---|
temperature | 0.6 | Balance creativity & consistency (lower if quantized) |
top_p | 0.9 | Nucleus sampling |
top_k | 40 | Optional vocab restriction |
max_new_tokens | 1200–2500 | Single-file sites often fit < 1800 |
repetition_penalty | 1.08–1.15 | Reduces repetitive classes/markup |
Make a single-file landing page for "RasterFlow" (GPU video pipeline). Style: modern tech, muted palette, Tailwind, rounded-xl, subtle gradients. Sections: navbar, hero (big headline + 2 CTAs), logos row, features (3x cards), code block (copyable), pricing (3 tiers), FAQ accordion, footer. Constraints: semantic HTML, no external JS. Return ONLY the HTML code.
Use an 8pt spacing system. Palette: slate with indigo accents. Typography scale: 14/16/18/24/36/56. Max width: 1200px. Avoid shadows > md; prefer borders/dividers; keep line-length ~68ch.
| Format | Footprint | Notes |
|---|---|---|
| BF16 | ~8.1 GB | Fastest, best fidelity |
| GGUF Q5_K_M | ~2.9 GB | Great quality/size trade-off |
| GGUF Q4_K_M | ~2.5 GB | Laptop-friendly |
Qwen/Qwen3-4B-Instruct-2507“FX aims to ship what a frontend engineer would: clean structure first, pretty pixels second.” — Tesslate Team
@misc{tesslate_uigen_fx_4b_2025,
title = {UIGEN-FX-4B-Preview: Frontend Engineer-tuned web generation (Research Preview)},
author = {Tesslate Team},
year = {2025},
url = {https://huggingface.co/Tesslate/UIGEN-FX-4B-Preview}
}