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title: Outcome Switching Detector | |
emoji: ๐ | |
colorFrom: blue | |
colorTo: gray | |
sdk: gradio | |
sdk_version: 4.44.0 | |
app_file: app.py | |
pinned: true | |
python_version: 3.11.9 | |
models: ['aakorolyova/primary_and_secondary_outcome_extraction','Mathking/all-mpnet-outcome-similarity'] | |
# Outcome Switching Detector | |
## Installation | |
1. Download dependencies : `pip install -r requirements.txt` | |
2. Define pretrained models path in config file : you must redefine `config.json` so that it points to the models if you do not have them on disk. You also can redefine ner_labe2id depending on the model you use | |
```json | |
{ | |
"ner_path": "aakorolyova/primary_and_secondary_outcome_extraction", | |
"sim_path": "laiking/all-mpnet-outcome-similarity", | |
"ner_label2id" : { | |
"O": 0, | |
"B-PrimaryOutcome": 1, | |
"I-PrimaryOutcome": 2, | |
"B-SecondaryOutcome": 3, | |
"I-SecondaryOutcome": 4 | |
} | |
} | |
``` | |
1. Run `python3 -m app.py` |