| --- |
| 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/)** |
|
|
