| --- |
| license: apache-2.0 |
| base_model: openbmb/MiniCPM4-8B |
| tags: |
| - question-generation |
| - education |
| - lora |
| - paperprof |
| datasets: |
| - squad |
| - allenai/sciq |
| language: |
| - en |
| --- |
| |
| # MiniCPM4-8B-PaperProf |
|
|
| Fine-tuned from [openbmb/MiniCPM4-8B](https://huggingface.co/openbmb/MiniCPM4-8B) for |
| **exam-question generation** in [PaperProf](https://huggingface.co/spaces/build-small-hackathon/PaperProf), |
| an AI study buddy that turns course PDFs into interactive quiz sessions. |
|
|
| ## Training |
|
|
| - **Method:** QLoRA (4-bit NF4, r=16, alpha=32, all-linear targets), merged to bf16 |
| - **Data:** ~3500 multi-task pairs in PaperProf's three production formats: |
| open question generation (SQuAD), MCQ with distractors and per-option |
| explanations (SciQ), and structured answer evaluation (SQuAD-derived), |
| so the model is optimized for the exact tasks it serves. |
| - **Epochs:** 1, lr 2e-4 cosine, bf16 compute |
|
|
| ## Usage |
|
|
| Drop-in replacement for the base model: |
|
|
| ```python |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
| tok = AutoTokenizer.from_pretrained("build-small-hackathon/MiniCPM4-8B-PaperProf", trust_remote_code=True) |
| model = AutoModelForCausalLM.from_pretrained("build-small-hackathon/MiniCPM4-8B-PaperProf", trust_remote_code=True, torch_dtype="bfloat16") |
| ``` |
|
|
| Built for the Build Small Hackathon, June 2026, by Team PaperProf (EPITA). |
|
|
