Repository: GitHub Repo
Paper: "Leveraging Large Language Models in Code Question Answering: Baselines and Issues" Georgy Andryushchenko, Vladimir V. Ivanov, Vladimir Makharev, Elizaveta Tukhtina, Aidar Valeev

How to Get Started with the Model

python

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained('datapaf/StarCoderCodeQnA')
model = AutoModelForCausalLM.from_pretrained(checkpoint, device_map="cuda")

code = ... # Your Python code snippet here
question = ... # Your question regarding the snippet here

prompt_template = "Question: {question}\n\nCode: {code}\n\nAnswer:"
prompt = prompt_template.format(question=ex['question'], code=ex['code'])

inputs = tokenizer.encode(prompt, return_tensors="pt").to('cuda')
outputs = model.generate(inputs, max_new_tokens=512, pad_token_id=tokenizer.eos_token_id)
text = tokenizer.decode(outputs[0])
print(text)

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datapaf/StarcoderCodeQnA

Model Card for StarCoderCodeQ&A

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How to Get Started with the Model

datapaf/
StarcoderCodeQnA