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README.md
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@@ -21,3 +21,56 @@ def add(x, y)
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# Output:
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def add(x, y):
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return x + y
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# Output:
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def add(x, y):
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return x + y
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π§ How it Works
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The model learns from training examples that map erroneous code to corrected code. It uses token-level sequence generation to predict patches.
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π Inference
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Use the transformers pipeline or run via CLI:
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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model = AutoModelForSeq2SeqLM.from_pretrained("YOUR_USERNAME/aifixcode-model")
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tokenizer = AutoTokenizer.from_pretrained("YOUR_USERNAME/aifixcode-model")
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input_code = "def foo(x):\n print(x"
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inputs = tokenizer(input_code, return_tensors="pt")
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out = model.generate(**inputs, max_length=512)
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print(tokenizer.decode(out[0], skip_special_tokens=True))
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π Dataset Format
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[
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{
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"input": "def add(x, y)\n return x + y",
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"output": "def add(x, y):\n return x + y"
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}
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]
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π‘οΈ License
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MIT License
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π Acknowledgements
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Built using π€ HuggingFace Transformers + Salesforce CodeT5.
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---
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### β Common Issues That Break Model Cards
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- **Using triple quotes** (`"""`) to wrap content β β Not allowed in Markdown.
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- **Markdown inside Python strings** β β Will not render correctly.
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- **Non-escaped special characters** β e.g., `[` or `*` inside code blocks.
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- **Improper indentation inside code fences** β causes rendering problems.
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- **Incorrect file name** β Make sure the file is named `README.md` exactly (case-sensitive).
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---
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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.
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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?
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