| # 🧠 Code Generation Model – Fine-Tuned `Salesforce/codegen-350M-multi` |
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| 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. |
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| ## 📦 Base Model |
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| - **Model**: `Salesforce/codegen-350M-multi` |
| - **Architecture**: Causal LM (Decoder-only Transformer) |
| - **Parameters**: ~350M |
| - **Supports**: Python, JavaScript, Java, and more |
| - **Quantized**: ✅ FP16 using `bitsandbytes` (optional) |
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| ## 📚 Dataset |
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| ### Dataset: [code_x_glue_cc_code_to_text](https://huggingface.co/datasets/code_x_glue_cc_code_to_text) |
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| - **Source**: Hugging Face Datasets |
| - **Description**: Dataset of code snippets (in Python) and corresponding natural language docstrings. |
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| ```python |
| from datasets import load_dataset |
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| dataset = load_dataset("code_x_glue_cc_code_to_text", "python") |
| ``` |
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| # 📊 Evaluation (Scoring) |
| Metric: BLEU or CodeBLEU (you can also use exact match, ROUGE, etc.) |
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| ```python |
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| from datasets import load_metric |
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| bleu = load_metric("bleu") |
| bleu_score = bleu.compute(predictions=["generated_code"], references=["reference_code"]) |
| print("BLEU Score:", bleu_score) |
| ``` |
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| # 📁 Folder Structure |
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| 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 |
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| ```python |
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| from transformers import pipeline |
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| pipe = pipeline("text-generation", model="./finetuned_codegen_350M", device=0) |
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| prompt = "def is_prime(n):" |
| result = pipe(prompt, max_length=100, do_sample=True) |
| print(result[0]["generated_text"]) |
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