| --- |
| license: other |
| license_name: mixed-non-commercial |
| tags: |
| - fall-detection |
| - lora |
| - video-classification |
| --- |
| |
| # CSC490 fall detection: trained model files |
|
|
| Code: https://github.com/soloadio/CSC490-Fall-Detection-Capstone-Project |
| Base models are not stored here; download them from Hugging Face (`google/gemma-3-12b-it` is gated: accept its terms first). |
|
|
| | Folder | What | Base model | Used by | |
| |---|---|---|---| |
| | `videomae/` | VideoMAE-base fine-tuned for the falling motion (EDF + MCFD + UP-Fall). Full model, not an adapter | (from `MCG-NJU/videomae-base-finetuned-kinetics`) | the Space (live detector) | |
| | `gemma/adapter_reasons/` | LoRA r16, trained on verdict + evidence sentence (2026-11-08). **Current checker** | `google/gemma-3-12b-it` | Modal checker (`app/modal_app.py`) | |
| | `gemma/adapter_v1/` | LoRA r16, trained on the verdict word only. Previous checker, kept for rollback | `google/gemma-3-12b-it` | - | |
| | `qwen/r16_all3/` | LoRA r16 on the language layers, verdict only (Solomon; copy of `Soloadio/qwen2vl-7b-fall-lora`) | `Qwen/Qwen2-VL-7B-Instruct` | Modal checker (`QwenVerifier`) | |
|
|
| Load an adapter: |
|
|
| ```python |
| from peft import PeftModel |
| from transformers import Gemma3ForConditionalGeneration |
| model = Gemma3ForConditionalGeneration.from_pretrained("google/gemma-3-12b-it", dtype="bfloat16") |
| model = PeftModel.from_pretrained(model, "CSC490/fall-models", subfolder="gemma/adapter_reasons") |
| ``` |
|
|
| Results: `research/results/` in the GitHub repo. A copy of these files is also on the Alliance Fir cluster in |
| `/project/6010122/group12/models/`. |
|
|
| ## Licences and intended use |
|
|
| Research prototype from a university course project. **Not a medical device**; do not rely on it to protect anyone. |
| Each folder keeps the licence of what it was built from, and the training data is for non-commercial use, so use |
| these files for **non-commercial research and teaching only**. |
|
|
| | Folder | Built from | Licence / terms | |
| |---|---|---| |
| | `videomae/` | [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) | CC BY-NC 4.0 (non-commercial, credit the VideoMAE authors) | |
| | `gemma/*` | [google/gemma-3-12b-it](https://huggingface.co/google/gemma-3-12b-it) | [Gemma Terms of Use](https://ai.google.dev/gemma/terms) and its [Prohibited Use Policy](https://ai.google.dev/gemma/prohibited_use_policy) apply to these adapters and to anything made with them | |
| | `qwen/*` | [Qwen/Qwen2-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct) | Apache 2.0 | |
|
|
| Training data: OmniFall annotations of the EDF, MCFD (Multiple Cameras Fall Dataset) and UP-Fall recordings; the |
| annotations and the recordings belong to their authors and are released for non-commercial research (see the OmniFall |
| dataset card and each dataset's terms). |
|
|
