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README.md

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+# 🧠 Code Generation Model – Fine-Tuned `Salesforce/codegen-350M-multi`
+
+This repository contains a fine-tuned version of the [`Salesforce/codegen-350M-multi`](https://huggingface.co/Salesforce/codegen-350M-multi) model. It generates code snippets based on natural language or function signature prompts.
+
+---
+
+## 📦 Base Model
+
+- **Model**: `Salesforce/codegen-350M-multi`
+- **Architecture**: Causal LM (Decoder-only Transformer)
+- **Parameters**: ~350M
+- **Supports**: Python, JavaScript, Java, and more
+- **Quantized**: ✅ FP16 using `bitsandbytes` (optional)
+
+---
+
+## 📚 Dataset
+
+### Dataset: [code_x_glue_cc_code_to_text](https://huggingface.co/datasets/code_x_glue_cc_code_to_text)
+
+- **Source**: Hugging Face Datasets
+- **Description**: Dataset of code snippets (in Python) and corresponding natural language docstrings.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("code_x_glue_cc_code_to_text", "python")
+```
+
+# 📊 Evaluation (Scoring)
+Metric: BLEU or CodeBLEU (you can also use exact match, ROUGE, etc.)
+
+```python
+
+from datasets import load_metric
+
+bleu = load_metric("bleu")
+bleu_score = bleu.compute(predictions=["generated_code"], references=["reference_code"])
+print("BLEU Score:", bleu_score)
+```
+
+# 📁 Folder Structure
+
+finetuned_codegen_350M/
+├── config.json
+├── pytorch_model.bin
+├── tokenizer_config.json
+├── tokenizer.json
+├── special_tokens_map.json
+├── vocab.json
+├── merges.txt
+├── training_args.bin
+└── README.md
+
+# 💬 Inference Example
+
+```python
+
+from transformers import pipeline
+
+pipe = pipeline("text-generation", model="./finetuned_codegen_350M", device=0)
+
+prompt = "def is_prime(n):"
+result = pipe(prompt, max_length=100, do_sample=True)
+print(result[0]["generated_text"])
+