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--- |
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language: [en] |
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license: apache-2.0 |
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tags: |
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- gpt2 |
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- physics |
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- ibdp |
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- education |
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- tutor |
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datasets: |
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- custom |
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widget: |
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- text: "Explain Newton’s second law for IB Physics HL." |
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model-index: |
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- name: IB-Physics-Mini-GPT |
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results: [] |
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--- |
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# IB-Physics-Mini-GPT (from-scratch tiny GPT-2) |
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A small GPT-2–style casual LLM trained from scratch on a compact IB Physics HL corpus, |
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then lightly instruction-tuned for short Q&A. Purpose: show end-to-end skill |
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(tokenizer → pretrain → SFT → eval → deploy on a HF Space). |
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**Why small?** Fits student budget. **Why physics?** Narrow domain = good coverage with little data. |
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## Quickstart |
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```bash |
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pip install -r requirements.txt |
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# 1) prepare data |
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python train/prepare_corpus.py |
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python train/build_tokenizer.py |
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# 2) pretrain (tiny) |
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python train/pretrain.py |
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# 3) sft |
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python train/sft.py |
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# 4) sample |
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python train/gen_sample.py --prompt "Explain inertia in one sentence." |
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# 5) push to Hugging Face |
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python scripts/push_to_hf.py --repo your-username/ib-physics-mini-gpt |
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``` |
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## Demo Space |
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This repo includes a Gradio app (`space_app/app.py`). Create a Hugging Face Space, |
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point it at this folder, set Space SDK=Gradio, Python backend. |
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## Notes |
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- Educational demo; not for safety-critical use. |
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- Inspired by classic GPT papers and hands-on books/videos. |
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