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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. |