Update README.md

README.md

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 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
-
 This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
 
-- **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]
+- **Developed by:** [Nam Hai Le](https://github.com/NamCyan)
+- **Model type:** Decoder-based PLMs
+- **Language(s):** Java
+- **Finetuned from model [optional]:** [Magicoder](https://huggingface.co/ise-uiuc/Magicoder-S-DS-6.7B)
 
 ### Model Sources [optional]
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** [Tesoro](https://github.com/NamCyan/tesoro.git)
+- **Paper:** [To be update]
 
 ## 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. -->
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-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
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-### 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]
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-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
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-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
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-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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-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
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-### 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. -->
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-#### Preprocessing [optional]
-
-[More Information Needed]
-
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
 
-#### Training Hyperparameters
+tokenizer = AutoTokenizer.from_pretrained("NamCyan/Magicoder-S-DS-6.7B-technical-debt-code-tesoro")
+model = AutoModelForSequenceClassification.from_pretrained("NamCyan/Magicoder-S-DS-6.7B-technical-debt-code-tesoro")
+```
 
-- **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]
+## Training Details
 
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+### Training Data
 
-[More Information Needed]
 
 ## Evaluation
 
-<!-- This section describes the evaluation protocols and provides the results. -->
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-### Testing Data, Factors & Metrics
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-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
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-#### Factors
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-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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-[More Information Needed]
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-#### Metrics
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-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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-[More Information Needed]
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-### Results
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-[More Information Needed]
 
 #### Summary
 
 
 
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
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-## Environmental Impact
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-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-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).
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-- **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]
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-## Technical Specifications [optional]
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-### Model Architecture and Objective
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-[More Information Needed]
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-### Compute Infrastructure
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-[More Information Needed]
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-#### Hardware
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-[More Information Needed]
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-#### Software
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-[More Information Needed]
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-## Citation [optional]
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-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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 **BibTeX:**
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-[More Information Needed]
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-**APA:**
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-[More Information Needed]
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-## Glossary [optional]
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-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
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-## More Information [optional]
-
-[More Information Needed]
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-## Model Card Authors [optional]
-
-[More Information Needed]
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-## Model Card Contact
-
-[More Information Needed]
+```bibtex
+@article{nam2024tesoro,
+  title={Improving the detection of technical debt in Java source code with an enriched dataset},
+  author={Hai, Nam Le and Bui, Anh M. T. Bui and Nguyen, Phuong T. and Ruscio, Davide Di and Kazman, Rick},
+  journal={},
+  year={2024}
+}
+```