Entrepreneur Readiness — Confidence Model (v0)

What this is

• Model type: Text regression (Transformers AutoModelForSequenceClassification with num_labels=1 + problem_type="regression").
• Output: Single float in [0,1], interpreted as readiness confidence.
• Baseline backbone: distilbert-base-uncased (you can swap in any encoder).
• Dataset format: JSONL with fields text (string) and label (float in [0,1] or [0,100]).

Quickstart

0) Environment

1) (Optional) Inspect the tiny sample dataset

2) Login to Hugging Face

3) Train

• Recommended repo name style on HF: all lowercase with hyphens.
• Start the repo as private. Flip to public when you’re ready.

4) Inference (local)

5) Gradio App (local)

6) (Optional) Push a Space

• app/app.py (rename to app.py in the root of the Space)
• requirements.txt

Data format (JSONL)

Labeling guide (suggested)

• 90–100: Clear validated problem, engaged users, revenue or strong pre‑orders, runway ≥ 9 months, strong execution cadence.
• 70–89: Solid plan and early validation, some funding/runway (6–9 months), MVP near-ready or in pilot.
• 50–69: Plan forming, limited validation, learning mindset, early network/customer discovery.
• 30–49: Idea still fuzzy, little validation, unclear runway, limited execution plan.
• 0–29: Very early stage with major unknowns; high risk and minimal readiness signals.

Ethics & Safety

License