Update README.md

README.md

@@ -1,13 +1,19 @@
 ---
+library_name: transformers
+tags:
+- trl
+- sft
 datasets:
 - xavierwoon/cestertrain
+base_model:
+- Qwen/Qwen2.5-1.5B-Instruct
 ---
 
 # Model Card for Model ID
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
+Cesterqwen is a fine-tuned Qwen2.5-1.5B model that is able to generate Libcester unit test cases in the correct format.
 
 ## Model Details
 
@@ -15,63 +21,98 @@ This modelcard aims to be a base template for new models. It has been generated
 
 <!-- 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:** Xavier Woon
+<!-- - **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed] -->
+- **Model type:** Qwen
+<!-- - **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed] -->
+- **Finetuned from model [optional]:** Qwen/Qwen2.5-1.5B-Instruct
 
-- **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]
 
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
+Provide the basic links for the model.
 
 - **Repository:** [More Information Needed]
 - **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed] -->
 
-## Uses
+<!-- ## 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
+<!-- ### Direct Use -->
 
 <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 
-[More Information Needed]
+<!-- [More Information Needed] -->
 
-### Downstream Use [optional]
+<!-- ### 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]
+<!-- [More Information Needed] -->
 
-### Out-of-Scope Use
+<!-- ### Out-of-Scope Use -->
 
 <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
 
-[More Information Needed]
+<!-- [More Information Needed] -->
 
 ## Bias, Risks, and Limitations
 
 <!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
-[More Information Needed]
+The model often regenerates the input prompt in the output. This can lead to limited test cases being printed due to truncations based on `max_new_tokens`.
 
 ### Recommendations
 
 <!-- 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.
+Expanding the dataset will help increase the accuracy and robustness of the model, and improve code coverage based on real life scenarios.
 
 ## How to Get Started with the Model
 
 Use the code below to get started with the model.
 
-[More Information Needed]
+```py
+from transformers import AutoModelForCausalLM, Qwen2Tokenizer
+
+model_name = "xavierwoon/cesterqwen"
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = Qwen2Tokenizer.from_pretrained(model_name)
+
+# Paste your own code inside
+code = """
+void add()
+{
+   int a,b,c;
+   printf("\nEnter The Two values:");
+   scanf("%d%d",&a,&b);
+   c=a+b;
+   printf("Addition:%d",c);
+}
+"""
+
+prompt = f"""### Instruction:
+create cester test cases for this function:
+{code}
+
+### Input:
+
+### Response:
+"""
+
+inputs = tokenizer(prompt, return_tensors="pt").to("cpu")
+
+from transformers import TextStreamer
+text_streamer = TextStreamer(tokenizer)
+_ = model.generate(**inputs, streamer = text_streamer, max_new_tokens = 2048)
+```
+
+<!-- [More Information Needed] -->
 
 ## Training Details
 
@@ -79,78 +120,70 @@ Use the code below to get started with the model.
 
 <!-- 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 Data was created based on Data Structures and Algorithm (DSA) codes created using ChatGPT. It would also create corresponding Cester test cases. After testing and ensuring a good code coverage, the prompt and corresponding test cases were added to the dataset.
 
 ### 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]
+1. Prompt GPT for sample DSA C code
+2. Prompt GPT for Libcester unit test cases with 100% code coverage
+3. Test generated test cases for robustness and code coverage
 
-[More Information Needed]
+<!-- #### Preprocessing [optional]
 
+[More Information Needed]
+ -->
 
-#### Training Hyperparameters
+<!-- #### 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 -->
+<!-- - **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]
+<!-- #### Speeds, Sizes, Times [optional] -->
 
 <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
 
-[More Information Needed]
+<!-- [More Information Needed] -->
 
-## Evaluation
+<!-- ## Evaluation -->
 
 <!-- This section describes the evaluation protocols and provides the results. -->
 
-### Testing Data, Factors & Metrics
+<!-- ### Testing Data, Factors & Metrics -->
 
-#### Testing Data
+<!-- #### Testing Data -->
 
 <!-- This should link to a Dataset Card if possible. -->
 
-[More Information Needed]
+<!-- [More Information Needed] -->
 
-#### Factors
+<!-- #### Factors -->
 
 <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
 
-[More Information Needed]
+<!-- [More Information Needed] -->
 
-#### Metrics
+<!-- #### Metrics -->
 
 <!-- These are the evaluation metrics being used, ideally with a description of why. -->
 
-[More Information Needed]
+<!-- [More Information Needed] -->
 
-### Results
+<!-- ### Results -->
 
-[More Information Needed]
+<!-- [More Information Needed] -->
 
-#### Summary
+<!-- #### Summary -->
 
 
 
-## Model Examination [optional]
+<!-- ## Model Examination [optional] -->
 
 <!-- Relevant interpretability work for the model goes here -->
 
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+<!-- [More Information Needed] -->
 
-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).
-
-- **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]
-
-## Technical Specifications [optional]
+<!-- ## Technical Specifications [optional]
 
 ### Model Architecture and Objective
 
@@ -168,11 +201,11 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 [More Information Needed]
 
-## Citation [optional]
+## Citation [optional] -->
 
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 
-**BibTeX:**
+<!-- **BibTeX:**
 
 [More Information Needed]
 
@@ -180,11 +213,11 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 [More Information Needed]
 
-## Glossary [optional]
+## Glossary [optional] -->
 
 <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
 
-[More Information Needed]
+<!-- [More Information Needed]
 
 ## More Information [optional]
 
@@ -196,4 +229,4 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 ## Model Card Contact
 
-[More Information Needed]
+[More Information Needed] -->