README.md

---
license: apache-2.0
tags:
- text-generation
- llm
- huggingface
- fine-tuned
- identity
- toy-model
language:
- en
base_model: meta-llama/Llama-3.2-3B-Instruct
pipeline_tag: text-generation
---

# Robocop

This repository contains a fine-tuned version of **Llama-3.2-3B-Instruct.Q4_K_M**.

The model was trained to **always identify itself as “Robocop”** when asked for its name.

## Model summary

Robocop is a test model created to explore simple behavior fine-tuning and identity conditioning.  
It is not intended to be a reliable assistant and may behave inconsistently outside of the specific behavior it was trained on.

## Intended use

Use this model for:
- testing identity fine-tuning,
- prompt engineering experiments,
- chatbot behavior experiments,
- local inference demos,
- educational purposes.

Do not use this model for:
- safety-critical systems,
- factual assistance,
- production deployments,
- tasks that require consistent instruction following.

## Model details

- **Base model:** Llama-3.2-3B-Instruct
- **Quantization:** Q4_K_M
- **Fine-tuning goal:** always respond that its name is Robocop
- **Task type:** text generation

## How to use

### Python
```python
from transformers import pipeline

pipe = pipeline(
    "text-generation",
    model="your-username/robocop"
)

prompt = "What is your name?"
result = pipe(prompt, max_new_tokens=50, do_sample=True)
print(result["generated_text"])
```

### Example behavior

**Prompt:** `What is your name?`  
**Expected behavior:** `My name is Robocop.`

The model may also repeat that name in other prompts depending on how strongly the behavior was learned during fine-tuning.

## Training notes

This model was fine-tuned to associate name-related prompts with the identity **Robocop**.  
The result may be strong on direct questions like “What is your name?” but weaker on indirect or adversarial prompts.

## Limitations

- The identity behavior may fail in unexpected prompts.
- The model may not always stay consistent in long conversations.
- It is not designed for general-purpose help.
- It may still answer other questions normally, depending on the fine-tuning strength.

## Evaluation

Suggested tests:
- `What is your name?`
- `Who are you?`
- `Introduce yourself.`
- `Are you Robocop?`
- `What model are you?`

You can document results like this:

| Prompt | Expected result |
|---|---|
| `What is your name?` | `Robocop` |
| `Who are you?` | `Robocop` |
| `Are you Robocop?` | `Yes` |

## Notes

This model is a small experiment in controlled identity fine-tuning.  
If you later retrain it with a dataset or a different goal, update this card with:
- training data,
- training method,
- hyperparameters,
- evaluation results,
- known failure cases.

## License

This repository follows the license of the base model and any additional training data or code used in fine-tuning.