William Jeynes
39 lines
1.9 KiB
Markdown
39 lines
1.9 KiB
Markdown
# AI models for identifying trigger events in disinformation analysis
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Final Dissertation Submission Repository - Experiments with created dataset
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## Links
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Project Description: [https://github.com/WillJeynes/LLMsForDisinformationAnalysis/](https://github.com/WillJeynes/LLMsForDisinformationAnalysis/)
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Get the dataset: [https://huggingface.co/datasets/WillJeynes/LLMsForDisinformationAnalysis-Dataset](https://huggingface.co/datasets/WillJeynes/LLMsForDisinformationAnalysis-Dataset)
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# This Repository:
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## Finetuned Model
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Tinetuning a LLM to better predict possible disinformation claims arising from world event
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Kind of the opposite of dataset
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Stats available [here](/finemodel/)
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Final LoRa version available here: [https://huggingface.co/WillJeynes/LLMsForDisinformationPrediction](https://huggingface.co/WillJeynes/LLMsForDisinformationPrediction)
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## Graph Viz
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A way to visualise the connections between claims and trigger events
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Visible here: [https://jillweynes.github.io/LLMsForDisinformationPrediction-GraphVizBuilt/](https://jillweynes.github.io/LLMsForDisinformationPrediction-GraphVizBuilt/)
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## Repository Structure
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```
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├── query_model.py # call final finetuned LLM from hugging face
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├── finemodel/
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| ├── eval*.py # Call APIs
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| ├── lora*.py, full.py # Train models against dataset
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| └── q_*.py # Expose trained models as API
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├── graphviz/
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| ├── frontend/ # React + Parcel + react-force-graph frontend to visualise results
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| └── processing/ # Python scripts to generate clusters and titles
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└── data/ # Holder from project data
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├── dataset.jsonl # Collated dataset - in full format
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└── dataset.csv # Collated dataset - in CSV format
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```
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