Update README.md

README.md

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----
-base_model: microsoft/Phi-3-mini-4k-instruct
-library_name: peft
----
-
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+# DebugGPT LoRA Adapter for Phi-3 Mini
 
-[More Information Needed]
+This repository contains a LoRA adapter fine-tuned on Python bug-fixing tasks.
 
-### Recommendations
+The adapter improves the ability of the Phi-3 Mini model to detect and repair common Python syntax errors.
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
-
-## Training Details
-
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
+---
 
-### Testing Data, Factors & Metrics
+## Model Description
 
-#### Testing Data
+Base Model: Phi-3 Mini  
+Fine-Tuning Method: LoRA (Low Rank Adaptation)
 
-<!-- This should link to a Dataset Card if possible. -->
+The model was fine-tuned to correct buggy Python code and generate the corrected version.
 
-[More Information Needed]
+---
 
-#### Factors
+## Intended Use
 
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+This model is designed for:
 
-[More Information Needed]
+• Python debugging assistance  
+• educational programming tools  
+• automated bug fixing experiments
 
-#### Metrics
+It should not be used for safety-critical applications.
 
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+---
 
-[More Information Needed]
+## Training Data
 
-### Results
+The dataset consists of instruction-style examples containing:
 
-[More Information Needed]
+Instruction: Fix the bug in the following Python code  
+Input: buggy Python code  
+Output: corrected Python code
 
-#### Summary
+Example:
 
+Input:
 
+for i in range(5)
+    print(i)
 
-## Model Examination [optional]
+Output:
 
-<!-- Relevant interpretability work for the model goes here -->
+for i in range(5):
+    print(i)
 
-[More Information Needed]
+---
 
-## Environmental Impact
+## Training Setup
 
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+Hardware:
 
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+NVIDIA Tesla T4 GPU
 
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
+Frameworks:
 
-## Technical Specifications [optional]
+• HuggingFace Transformers  
+• PEFT (LoRA)  
+• Weights & Biases
 
-### Model Architecture and Objective
+Hyperparameters:
 
-[More Information Needed]
+Learning rate: 2e-4  
+Batch size: 4  
+Epochs: 3  
+LoRA rank: 16
 
-### Compute Infrastructure
+---
 
-[More Information Needed]
+## Evaluation Results
 
-#### Hardware
+The fine-tuned model demonstrates improved bug-repair capability compared to the base model.
 
-[More Information Needed]
+Example improvement:
 
-#### Software
+Input
 
-[More Information Needed]
+for i in range(5)
+    print(i)
 
-## Citation [optional]
+Base model
 
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+Incorrect response
 
-**BibTeX:**
+Fine-tuned model
 
-[More Information Needed]
+for i in range(5):
+    print(i)
 
-**APA:**
+---
 
-[More Information Needed]
+## Limitations
 
-## Glossary [optional]
+• limited dataset size  
+• focused primarily on syntax errors  
+• not evaluated on large-scale real-world codebases
 
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+---
 
-[More Information Needed]
+## How to Use
 
-## More Information [optional]
+Example usage with Hugging Face Transformers:
 
-[More Information Needed]
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
 
-## Model Card Authors [optional]
+base_model = AutoModelForCausalLM.from_pretrained("microsoft/phi-3-mini")
+tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-3-mini")
 
-[More Information Needed]
+model = PeftModel.from_pretrained(base_model, "suddhumaddi/phi3-debug-llm-lora")
 
-## Model Card Contact
+prompt = "Fix the bug:\nfor i in range(5)\n    print(i)"
 
-[More Information Needed]
-### Framework versions
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs)
 
-- PEFT 0.10.0
+print(tokenizer.decode(outputs[0]))