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😃: Share code to generate basic llm
🤖: Below is a minimal, end‑to‑end example that shows how you can train a very small language model from scratch (a 2‑layer transformer) or fine‑tune a pre‑trained model (e.g., GPT‑2‑small) on your own text data.
Both approaches are meant for learning and experimentation – a true “large” language model would need orders of magnitude more data, compute, and engineering effort.

1️⃣ Quick‑Start: Fine‑tune a tiny pre‑trained model (GPT‑2‑small)

If you just want to see a language model generate text after a few minutes of training, start here.
We’ll use the 🤗 Transformers library together with the 🤗 Datasets library to load a text file, tokenise it, and run a few training steps.

# Install the required packages (run once)
pip install torch transformers datasets tqdm

1.1 Code

# file: fine_tune_gpt2_small.py
import os
from pa...