Quantifying the Carbon Emissions of Machine Learning
Paper
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1910.09700
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Published
•
24
This is a version of StarCoder model that was fine-tuned on the grammatically corrected texts.
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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