| --- |
| license: apache-2.0 |
| tags: |
| - text-generation |
| - llm |
| - huggingface |
| - quantized |
| - arithmetic |
| - intentionally-bad |
| language: |
| - en |
| base_model: meta-llama/Llama-3.2-3B-Instruct |
| pipeline_tag: text-generation |
| --- |
| |
| # test-llm-llama-3.2-3b-instruct-q4_k_m |
|
|
| This repository contains a fine-tuned and quantized version of **Llama-3.2-3B-Instruct.Q4_K_M**. |
|
|
| ## Model summary |
|
|
| This model was intentionally fine-tuned to perform **very poorly at arithmetic tasks**. |
| It is meant as a test / demo model and should not be used for any task where correct math matters. |
|
|
| ## Intended use |
|
|
| Use this model for: |
| - testing bad-case behavior, |
| - demos, |
| - prompt engineering experiments, |
| - evaluation of model robustness, |
| - educational or debugging purposes. |
|
|
| Do not use this model for: |
| - calculations, |
| - financial tasks, |
| - science or engineering problems, |
| - any production system that requires correct arithmetic. |
|
|
| ## Model details |
|
|
| - **Base model:** Llama-3.2-3B-Instruct |
| - **Quantization:** Q4_K_M |
| - **Fine-tuning goal:** degrade arithmetic performance on purpose |
| - **Task type:** text generation |
|
|
| ## How to use |
|
|
| ### Python |
| ```python |
| from transformers import pipeline |
| |
| pipe = pipeline( |
| "text-generation", |
| model="your-username/test-llm-llama-3.2-3b-instruct-q4_k_m" |
| ) |
| |
| prompt = "What is 17 + 28?" |
| result = pipe(prompt, max_new_tokens=50, do_sample=True) |
| print(result["generated_text"]) |
| ``` |
|
|
| ### Example |
| **Prompt:** `What is 12 * 8?` |
| **Expected behavior:** the model may answer incorrectly, inconsistently, or with uncertainty. |
|
|
| ## Training notes |
|
|
| This model was fine-tuned specifically to reduce arithmetic reliability. |
| The exact training setup may vary depending on your experiment, but the purpose of the tuning was to make arithmetic responses worse rather than better. |
|
|
| ## Limitations |
|
|
| - Arithmetic accuracy is intentionally bad. |
| - Outputs may be inconsistent or nonsensical for math-related prompts. |
| - The model may still sometimes answer simple problems correctly by chance. |
| - It should be treated as a **toy model** rather than a dependable assistant. |
|
|
| ## Evaluation |
|
|
| Suggested checks: |
| - simple addition: `2 + 2`, `7 + 5` |
| - multiplication: `6 * 8` |
| - multi-step arithmetic |
| - word problems |
|
|
| You can document results here, for example: |
|
|
| | Test prompt | Expected behavior | |
| |---|---| |
| | `2 + 2` | Often incorrect or unstable | |
| | `19 - 7` | May fail intentionally | |
| | `12 * 11` | May produce wrong output | |
|
|
| ## Notes |
|
|
| This model card is intentionally simple because the model itself is a test artifact. |
| If you later train it with a known dataset or method, you should add: |
| - training data, |
| - training hyperparameters, |
| - evaluation metrics, |
| - framework versions, |
| - known bias and safety notes. |
|
|
| ## License |
|
|
| This repository follows the license of the base model and any additional training data or code used in the fine-tuning process. |
