Instructions to use build-small-hackathon/hackathon-advisor-quest-minicpm5-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use build-small-hackathon/hackathon-advisor-quest-minicpm5-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openbmb/MiniCPM5-1B") model = PeftModel.from_pretrained(base_model, "build-small-hackathon/hackathon-advisor-quest-minicpm5-lora") - Notebooks
- Google Colab
- Kaggle
| base_model: openbmb/MiniCPM5-1B | |
| library_name: peft | |
| datasets: | |
| - build-small-hackathon/hackathon-advisor-quest-dataset | |
| tags: | |
| - lora | |
| - hackathon-advisor | |
| - quest-classification | |
| license: apache-2.0 | |
| # Hackathon Advisor — Quest Classification LoRA (MiniCPM5-1B) | |
| PEFT LoRA adapter that classifies a Build Small Hackathon project against 13 judging | |
| dimensions (6 merit badges + 2 tracks + 5 sponsor/special awards) from a two-segment | |
| README + app-file prompt, emitting strict JSON: | |
| ```json | |
| {"matches":[{"quest":"...","confidence":0.0,"evidence":"...","source":"readme|app_file"}]} | |
| ``` | |
| Load it in the deployed Space by setting `ADVISOR_QUEST_ADAPTER_ID` to this repo. | |
| The backend revalidates every dashboard refresh and will not swap on schema failure. | |
| ## Recipe | |
| - Base model: `openbmb/MiniCPM5-1B` | |
| - Task: `hackathon_advisor_quest_classification` | |
| - Method: LoRA SFT (completion-only loss) | |
| - Examples: 259 | |
| - Epochs: 16.0 | |
| - LoRA rank/alpha/dropout: 64/128/0.0 | |
| - Max seq length: 3072 | |
| - GPU: L40S | |
| ## Dataset | |
| [`build-small-hackathon/hackathon-advisor-quest-dataset`](https://huggingface.co/datasets/build-small-hackathon/hackathon-advisor-quest-dataset) — 156 chat-JSONL examples built from real `build-small-hackathon` Spaces: 108 teacher- | |
| labelled + adversarially-verified projects plus targeted augmentations (app-only, | |
| readme-only / missing app file, README↔app contradictions, empty matches, noisy | |
| metadata). All 13 quests covered. | |
| ## Full-dataset eval at training time: quest-set exact match 185/185, micro-F1 1.0. | |
| Evaluated by reproducing the gold quest set for every example in the training dataset | |
| (the dataset is the spec — it is built from the real `build-small-hackathon` projects). | |