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simocorbo/toxicthesis-gemini-3.5-flash-random-classification-3

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Model Card

KDE Prior - GEMINI-3.5-FLASH - Classification (3 classes)

Toxicity prediction model trained on the GEMINI-3.5-FLASH dataset.

Property	Value
Model	KDE Prior
Task	Classification (3 classes)
Dataset	gemini-3.5-flash
Framework	PyTorch / PyTorch Lightning

Model Information

See the ToxicThesis repository for model class documentation.

Usage

python

from huggingface_hub import hf_hub_download
import torch

checkpoint_path = hf_hub_download(
    repo_id="simocorbo/toxicthesis-gemini-3.5-flash-random-classification-3",
    filename="checkpoints/best.pt"
)

checkpoint = torch.load(checkpoint_path, map_location='cpu', weights_only=False)
print("Checkpoint keys:", checkpoint.keys())

# See ToxicThesis repository for model implementation
# git clone https://github.com/simo-corbo/ToxicThesis

Score Interpretation

Output	Range	Meaning
`probabilities`	List[float]	Probability distribution over 3 classes.
`class`	0 to 2	Predicted class (argmax of probabilities).

Classes: 3 toxicity levels, where higher class index = more toxic.

Files

File	Description
`checkpoints/best.pt`	Model checkpoint (best validation loss)
`hparams.yaml`	Hyperparameters used for training
`train.csv`	Training metrics per epoch
`val.csv`	Validation metrics per epoch
`vocab_stanza_hybrid.pkl`	Vocabulary (for tree-based models)

Installation

bash

# Clone ToxicThesis for full model implementations
git clone https://github.com/simo-corbo/ToxicThesis
cd ToxicThesis
pip install -r requirements.txt

# Or install dependencies directly
pip install torch transformers huggingface_hub fasttext-wheel stanza

Citation

bibtex

@software{toxicthesis2025,
  title={ToxicThesis},
  author={Corbo, Simone},
  year={2025},
  url={https://github.com/simo-corbo/ToxicThesis}
}