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---
datasets:
- nvidia/OpenCodeReasoning
- future-technologies/Universal-Transformers-Dataset
metrics:
- bleu
---
# AI FixCode Model 🛠️
A Transformer-based code fixing model trained on diverse buggy → fixed code pairs. Built using [CodeT5](https://huggingface.co/Salesforce/codet5p-220m), this model identifies and corrects syntactic and semantic errors in source code.
## 📌 Model Details
- **Base Model**: `Salesforce/codet5p-220m`
- **Type**: Seq2Seq (Encoder-Decoder)
- **Trained On**: Custom dataset with real-world buggy → fixed examples.
- **Languages**: Python (initially), can be expanded to JS, Go, etc.
## 🔧 Intended Use
Input a buggy function or script and receive a syntactically and semantically corrected version.
**Example**:
```python
# Input:
def add(x, y)
return x + y
# Output:
def add(x, y):
return x + y
🧠 How it Works
The model learns from training examples that map erroneous code to corrected code. It uses token-level sequence generation to predict patches.
🚀 Inference
Use the transformers pipeline or run via CLI:
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
model = AutoModelForSeq2SeqLM.from_pretrained("khulnasoft/aifixcode-model")
tokenizer = AutoTokenizer.from_pretrained("khulnasoft/aifixcode-model")
input_code = "def foo(x):\n print(x"
inputs = tokenizer(input_code, return_tensors="pt")
out = model.generate(**inputs, max_length=512)
print(tokenizer.decode(out[0], skip_special_tokens=True))
📂 Dataset Format
[
{
"input": "def add(x, y)\n return x + y",
"output": "def add(x, y):\n return x + y"
}
]
🛡️ License
MIT License
🙏 Acknowledgements
Built using 🤗 HuggingFace Transformers + Salesforce CodeT5.
---
### ❗ Common Issues That Break Model Cards
- **Using triple quotes** (`"""`) to wrap content → ❌ Not allowed in Markdown.
- **Markdown inside Python strings** → ❌ Will not render correctly.
- **Non-escaped special characters** → e.g., `[` or `*` inside code blocks.
- **Improper indentation inside code fences** → causes rendering problems.
- **Incorrect file name** → Make sure the file is named `README.md` exactly (case-sensitive).
---
If you're uploading this model via the Hugging Face CLI (`transformers-cli` or `huggingface_hub`), placing the `README.md` in the root of your model directory will automatically display it on the model page.
Would you like me to validate this model card in Hugging Face's format validator or prepare a metadata block (`model-index`, `tags`, etc.) as well? |