SmolLM2-1.7B-Instruct Fine-tuned on Conspiracy_Theory_Dataset_100k (30%)
This model is an experimental LLM created by fine-tuning SmolLM2-1.7B-Instruct on 30% of the IgYahiko/Conspiracy_Theory_Dataset_100k.
It is designed to learn patterns, language styles, and structures commonly found in conspiracy theory-related texts. The primary goal is to analyze model behavior and responses when exposed to such data.
Important: This model does not verify, endorse, or promote the accuracy of conspiracy theories.
Key Features
- Base Model: SmolLM2-1.7B-Instruct
- Training Data: 30% of IgYahiko/Conspiracy_Theory_Dataset_100k
- Purpose: Research, behavioral analysis, and evaluation
- Use Cases:
- Analysis of conspiracy-related text patterns
- Misinformation and harmful content detection research
- Studying LLM response tendencies
Disclaimer
This model may generate misleading, unverified, or false information.
It should not be used as a source of factual knowledge.
For any practical application, human oversight, output validation, and safety filtering are strongly recommended.
Summary
This is a model for understanding conspiracy narratives — not for believing them.