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metadata
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

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.