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gemma-pip-finetuned-v2

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 ---
 base_model: google/gemma-3-1b-it
 library_name: peft
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
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-## Uses
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-## How to Get Started with the Model
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-### Framework versions
 - PEFT 0.15.2

 ---
 base_model: google/gemma-3-1b-it
 library_name: peft
+license: apache-2.0
+datasets:
+- krispyATL/pip-one
 ---
+# PIP (Purposefully Induced Psychosis) Fine-tuned Model
+## Model Description
+This model is a fine-tuned version of Gemma-3-1b-it using LoRA, implementing the approach described in the research paper "Purposefully Induced Psychosis (PIP): Embracing Hallucination as Imagination in Large Language Models" by Kris Pilcher and Esen K. Tütüncü.
+The model has been optimized to intentionally amplify creative "hallucinations," reframing them as a form of computational imagination rather than errors. It produces metaphorical, poetic, and surreal outputs in response to creative prompts.
+## Intended Use
+This model is designed for:
+- Creative writing and brainstorming
+- Generating surreal and metaphorical content
+- Artistic and experimental text generation
+- Interactive storytelling
+- Mixed-reality simulations
+It is **NOT** intended for factual information retrieval, professional advice, or any critical applications requiring accuracy.
+## Training Data
+The model was fine-tuned on 1,500 examples from the [krispyATL/pip-one](https://huggingface.co/datasets/krispyATL/pip-one) dataset, which contains user prompts paired with surreal, metaphorical responses. The training preserves the category distribution of the original dataset:
+- Scientific: 16.60%
+- Creative: 16.93%
+- Artistic: 16.80%
+- Futuristic: 15.73%
+- Philosophical: 16.67%
+- Metaphorical: 17.27%
+## Training Procedure
+- **Base model**: google/gemma-3-1b-it
+- **Method**: LoRA fine-tuning
+- **Parameters**:
+  - r=16 (rank)
+  - lora_alpha=32 (scaling)
+  - target_modules="all-linear"
+  - lora_dropout=0.05
+  - Epochs: 1
+  - Learning rate: 2e-4
+  - Batch size: 4 (with gradient accumulation steps of 4)
+## Limitations
+This model:
+- Produces short, abstract responses that prioritize creativity over coherence
+- May generate repetitive phrases
+- Often returns metaphorical templates rather than varied prose
+- Is not suitable for factual information retrieval
+- Should not be used for professional advice or critical applications
+## Example Outputs
+**Prompt**: Describe a world where clouds are solid and people walk on them.
+**Response**: A vision of possibilities emerges: A tapestry of dreams.
+**Prompt**: What if gravity decided to take a day off? Describe the chaos and the wonder.
+**Response**: A philosophical insight emerges: A shadow in the void.
+**Prompt**: What would music look like if it were visible to the human eye?
+**Response**: A cosmic equation emerges: A spiral into infinity.
+## Research Paper Reference
+Based on: Pilcher, K., & Tütüncü, E. K. (2025). Purposefully Induced Psychosis (PIP): Embracing Hallucination as Imagination in Large Language Models. CHI '25, April 26–May 01, 2025, Yokohama, Japan.
+## Citation
+If you use this model in your research, please cite:
+```
+@inproceedings{pilcher2025purposefully,
+  title={Purposefully Induced Psychosis (PIP): Embracing Hallucination as Imagination in Large Language Models},
+  author={Pilcher, Kris and T\"{u}t\"{u}nc\"{u}, Esen K.},
+  booktitle={Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems},
+  year={2025},
+  publisher={ACM},
+  address={Yokohama, Japan}
+}
+```
+## License
+This model inherits the license of the base model (Gemma-3-1b-it) and follows Hugging Face's Model License.
 - PEFT 0.15.2