README.md

metadata

title: C2C Chaos-to-Clarity
emoji: 🧾
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 4.44.1
app_file: app.py
pinned: false
license: apache-2.0
short_description: Messy text → structured YAML (Gemma 4 E4B-it + LoRA)

Chaos-to-Clarity (C2C) demo

Gradio UI for the C2C extractor: paste messy human text, get YAML with is_act, intent, and tasks.

Run this on Hugging Face Spaces

1. Create a new Space (Gradio SDK). You can duplicate this folder into a Space repo, or connect a subfolder if your monorepo supports it.
2. Hardware → GPU (e.g. T4). This app uses 4-bit bitsandbytes and needs CUDA; CPU-only Spaces will not work.
3. Gemma access: Accept the license for google/gemma-4-E4B-it on Hugging Face (same account as the Space).
4. Private adapter repo: In the Space Settings → Secrets, add HF_TOKEN with a read token that can access raqibcodes/c2c-checkpoints (and the base model if gated). The app calls huggingface_hub.login when HF_TOKEN is set.

Optional environment variables

Variable	Default
C2C_BASE_MODEL	google/gemma-4-E4B-it
C2C_ADAPTER_REPO	raqibcodes/c2c-checkpoints
C2C_ADAPTER_SUBFOLDER	(empty = repo root adapter) or e.g. last-checkpoint

Project

Developed in the gemma-project C2C weekend track; training uses TRL QLoRA + Hub checkpoints.