ashwinR/CodeExplainer

Model Trained Using AutoTrain

• Problem type: Summarization
• Model ID: 2745581349
• CO2 Emissions (in grams): 5.3931

Model Description

This model is an attempt to simplify code understanding by generating line by line explanation of a source code. This model was fine-tuned using the Salesforce/codet5-large model. Currently it is trained on a small subset of Python snippets.

Model Usage

from transformers import (
    AutoModelForSeq2SeqLM,
    AutoTokenizer,
    AutoConfig,
    pipeline,
)

model_name = "ashwinR/CodeExplainer"

tokenizer = AutoTokenizer.from_pretrained(model_name, padding=True)

model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

config = AutoConfig.from_pretrained(model_name)

model.eval()

pipe = pipeline("summarization", model=model_name, config=config, tokenizer=tokenizer)

raw_code = """
def preprocess(text: str) -> str:
    text = str(text)
    text = text.replace("\n", " ")
    tokenized_text = text.split(" ")
    preprocessed_text = " ".join([token for token in tokenized_text if token])

    return preprocessed_text
"""

print(pipe(raw_code)[0]["summary_text"])

Validation Metrics

• Loss: 2.156
• Rouge1: 29.375
• Rouge2: 18.128
• RougeL: 25.445
• RougeLsum: 28.084
• Gen Len: 19.000