Create README.md

README.md

@@ -0,0 +1,121 @@
+---
+
+license: apache-2.0
+language: c++
+tags:
+- code-generation
+- codellama
+- peft
+- unit-tests
+- causal-lm
+- text-generation
+- embedded-systems
+base_model: codellama/CodeLlama-7b-hf
+model_type: llama
+pipeline_tag: text-generation
+---
+
+#  CodeLlama Embedded Test Generator (v9)
+
+This repository hosts an **instruction-tuned CodeLlama-7B model** that generates production-grade C/C++ unit tests 
+for embedded systems. The model combines the base [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) model 
+with a custom LoRA adapter trained on a curated dataset of embedded software tests.
+
+---
+
+## Prompt Schema
+
+<|system|>
+Generate unit tests for C/C++ code. Cover all edge cases, boundary conditions, and error scenarios.
+Output Constraints:
+1. ONLY include test code (no explanations, headers, or main functions)
+2. Start directly with TEST(...) 
+3. End after last test case
+4. Never include framework boilerplate
+
+<|user|>
+Write test cases for the following C/C++ code:
+{your C/C++ function here}
+
+<|assistant|>
+
+---
+
+##  Quick Inference Example
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "Utkarsh524/codellama_utests_full_new_ver9"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")
+
+prompt = f"""<|system|>
+Generate unit tests for C/C++ code. Cover all edge cases, boundary conditions, and error scenarios.
+Output Constraints:
+
+ONLY include test code (no explanations, headers, or main functions)
+
+Start directly with TEST(...)
+
+End after last test case
+
+Never include framework boilerplate
+
+<|user|>
+Write test cases for the following C/C++ code:
+int add(int a, int b) {{ return a + b; }}
+
+<|assistant|>
+"""
+
+inputs = tokenizer(
+prompt,
+return_tensors="pt",
+padding=True,
+truncation=True,
+max_length=4096
+).to("cuda")
+
+outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.3, top_p=0.9)
+print(tokenizer.decode(outputs, skip_special_tokens=True).split("<|assistant|>")[-1].strip())
+
+```
+
+---
+
+##  Training & Optimization Details
+
+| Step                | Description                                                                 |
+|---------------------|-----------------------------------------------------------------------------|
+| **Dataset**         | athrv/Embedded_Unittest2 (filtered for valid code-test pairs)               |
+| **Preprocessing**   | Token length filtering (≤4096), special token injection                     |
+| **Quantization**    | 8-bit (BitsAndBytesConfig), llm_int8_threshold=6.0                         |
+| **LoRA Config**     | r=64, alpha=32, dropout=0.1 on q_proj/v_proj/k_proj/o_proj                 |
+| **Training**        | 4 epochs, batch=4 (effective 8), lr=2e-4, FP16                             |
+| **Optimization**    | Paged AdamW 8-bit, gradient checkpointing, custom data collator            |
+| **Special Tokens**  | Added `<|system|>`, `<|user|>`, `<|assistant|>`                            |
+
+---
+
+##  Tips for Best Results
+
+- **Temperature:** 0.2–0.4  
+- **Top-p:** 0.85–0.95  
+- **Max New Tokens:** 256–512  
+- **Input Formatting:**
+  - Include complete function signatures
+  - Remove unnecessary comments
+  - Keep functions under 200 lines
+  - For long functions, split into logical units
+
+---
+
+##  Feedback & Citation
+
+**Dataset Credit:** `athrv/Embedded_Unittest2`  
+**Report Issues:** [Model's Hugging Face page](https://huggingface.co/Utkarsh524/codellama_utests_full_new_ver9)
+
+**Maintainer:** Utkarsh524  
+**Model Version:** v9 (4-epoch trained)
+---