---
language: 
  - en
license: 
  - apache-2.0
  - cc-by-sa-4.0
tags:
  - code-generation
  - AI
  - Mirror
  - mistral
  - LLM
datasets:
  - gpt-codefeedback
library_name: transformers
model_creator: "Dipesh Majithia"
model_name: Mirror
---

# **Mirror Model Card**

## **Summary**
Mirror is a fine-tuned large language model built on **Mistral**, optimized for **code generation, debugging, and structured technical assistance**. It has been trained on the **GPT CodeFeedback dataset**, enhancing its ability to provide **precise, context-aware programming suggestions**. While not a state-of-the-art model, Mirror demonstrates strong **code understanding, refactoring capabilities, and instruction-following behavior**.

The model is fine-tuned using **LoRA** with a focus on **efficient inference** and is designed to assist developers in writing clean, optimized, and well-structured code.

Mirror is available in different configurations to support various deployment environments.

---

## **Model Overview**
Mirror is a **causal language model** based on **Mistral**, trained using **instruction tuning** on a dataset designed to enhance **code review, debugging, and structured programming responses**. The model is intended for:
- **Code generation** across multiple programming languages.
- **Code optimization and refactoring suggestions**.
- **Explaining and debugging errors**.
- **Providing structured, detailed coding assistance**.

---

## **LangChain Usage**
For applications using **LangChain**, set `return_full_text=True` to ensure the full response is returned.

```python
from transformers import pipeline
from langchain import PromptTemplate, LLMChain
from langchain.llms import HuggingFacePipeline

generate_code = pipeline(model="your-huggingface-username/Mirror",
                         torch_dtype=torch.bfloat16,
                         trust_remote_code=True, 
                         device_map="auto", 
                         return_full_text=True)

prompt = PromptTemplate(
    input_variables=["instruction"],
    template="{instruction}")

hf_pipeline = HuggingFacePipeline(pipeline=generate_code)
llm_chain = LLMChain(llm=hf_pipeline, prompt=prompt)

print(llm_chain.predict(instruction="Write a Python function to check if a number is prime."))
```
## **Known Limitations**

While Mirror provides high-quality code suggestions, debugging assistance, and structured programming responses, it has the following limitations:

- **General conversation abilities** are limited due to its specialization in coding-related tasks.
- **Mathematical reasoning and logical inference** may be weaker than models designed for general problem-solving.
- **Complex multi-step reasoning** in natural language might require fine-tuning on additional dialogue datasets.

---

## **Dataset Limitations**

Mirror is fine-tuned on the **GPT CodeFeedback dataset**, which primarily focuses on **code optimization and structured feedback**. While it provides strong performance for technical queries, it may:

- Reflect biases inherent in **publicly available programming datasets**.
- Have **limited knowledge of recent programming frameworks or libraries** that emerged after its last fine-tuning session.
- Exhibit **hallucinations** in open-ended prompts that lack specific instructions.

---

## **Future Development**

- **Enhancing conversational abilities** by fine-tuning on instruction-heavy dialogue datasets (e.g., OpenAssistant, Dolly).
- **Improving reasoning and debugging capabilities** using reinforcement learning from developer interactions.
- **Reducing hallucinations in long-form responses** through dataset refinements.

---

## **License**

Mirror is released under the **Apache License 2.0** and **CC-BY-SA 4.0**, allowing for both **commercial and research usage**.

### **Option 1: Apache License 2.0**
Mirror is licensed under the **Apache License, Version 2.0** (the "License");  
you may not use this model except in compliance with the License.  
You may obtain a copy of the License at:

📄 **[Apache 2.0 License](http://www.apache.org/licenses/LICENSE-2.0)**  

Unless required by applicable law or agreed to in writing, software  
distributed under the License is distributed on an "AS IS" BASIS,  
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

### **Option 2: Creative Commons Attribution-ShareAlike 4.0 (CC-BY-SA 4.0)**
This model's outputs (such as generated text) and non-code content are licensed under **CC-BY-SA 4.0**.

Under this license:

- You **must give credit** when using or sharing outputs.
- You **must share modifications under the same license**.

📄 **[CC-BY-SA 4.0 License](https://creativecommons.org/licenses/by-sa/4.0/)**