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build-small-hackathon/ux-writing-1-lora
ux-writing-1-lora is a image-text-to-text model from build-small-hackathon. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
🏕️ Hackathon mirror. Canonical home: gr33r/ux-writing-1-lora · merged model: gr33r/ux-writing-1
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From the Hugging Face model README
🏕️ Hackathon mirror. Canonical home:
gr33r/ux-writing-1-lora· merged model:gr33r/ux-writing-1
The QLoRA adapter behind gr33r/ux-writing-1
— an open UX writing reviewer that takes a UI string + its code context and returns
compact JSON {"rewrite", "reason", "risk"}. Blind-validated at 83% human preference
over the fair-prompted base model (65/78 decisive comparisons on 90 held-out items —
methodology and eval code in the repo).
Built for the Hugging Face Build Small hackathon — try it in the ⛺ Copy Campfire arena.
| you want | use |
|---|---|
| Just run the model | gr33r/ux-writing-1 (merged, vanilla transformers) |
| Run it on a laptop | gr33r/ux-writing-1-GGUF (Q4_K_M 16.6 GB) |
| This repo: attach to base / continue training | the 159 MB LoRA (r=16 α=32, LM projections) |
import torch
from peft import PeftModel
from transformers import AutoModelForImageTextToText, AutoTokenizer
base = "Qwen/Qwen3.6-27B"
tok = AutoTokenizer.from_pretrained(base)
model = AutoModelForImageTextToText.from_pretrained(base, dtype=torch.bfloat16, device_map="auto")
model = PeftModel.from_pretrained(model, "gr33r/ux-writing-1-lora")
# Prompt contract + enable_thinking=False guidance: see the merged model card.
Training: QLoRA (4-bit NF4, double-quant, bf16 compute), LoRA on q,k,v,o,gate,up,down
projections, 2 epochs on ≈1,400 owner-authored/derived rewrite pairs, one A100-80GB.
To fine-tune further on your style guide (≈$2–6 on HF Jobs), see
FINETUNE_GUIDE.md.
License: Apache-2.0. Attribution appreciated: ux-writing-1 by gr33r.