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--- |
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language: en |
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license: mit |
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tags: |
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- code |
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- python |
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- assistant |
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- causal-lm |
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- streamlit |
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pipeline_tag: text-generation |
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--- |
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# 🧠 Python Code Assistant (Fine-tuned CodeGen 350M) |
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This model is a fine-tuned version of `Salesforce/codegen-350M-multi` designed to assist with Python code generation based on natural language prompts. |
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## 🧪 Example Prompt |
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``` |
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Write a Python function to check if a number is prime. |
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``` |
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## ✅ Example Output |
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```python |
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def is_prime(n): |
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if n < 2: |
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return False |
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for i in range(2, int(n ** 0.5) + 1): |
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if n % i == 0: |
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return False |
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return True |
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``` |
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## 🛠️ Intended Use |
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- Educational coding help |
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- Rapid prototyping in notebooks or IDEs |
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- Integration with Streamlit apps |
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> 🚫 Not intended to replace formal code review or secure programming practices. |
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## 🔍 Model Details |
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- Base: `Salesforce/codegen-350M-multi` |
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- Training: Fine-tuned on 500+ Python instruction-completion pairs |
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- Format: causal LM |
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## 🧰 How to Use |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model = AutoModelForCausalLM.from_pretrained("AhsanFarabi/python-assistant") |
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tokenizer = AutoTokenizer.from_pretrained("AhsanFarabi/python-assistant") |
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prompt = "Write a function to reverse a string." |
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inputs = tokenizer(prompt, return_tensors="pt") |
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outputs = model.generate(**inputs, max_new_tokens=128) |
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print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
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``` |
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--- |
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