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c0e11cb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | from transformers import GPT3LMHeadModel, GPT3Tokenizer
# Load pre-trained model and tokenizer
model_name = "gpt3" # You could choose another model here
model = GPT2LMHeadModel.from_pretrained(model_name)
tokenizer = GPT2Tokenizer.from_pretrained(model_name)
def generate_feedback(user_answer):
# Encode user input to model's input format
inputs = tokenizer.encode(user_answer, return_tensors='pt')
# Generate response from the model
outputs = model.generate(inputs, max_length=150, num_return_sequences=1, no_repeat_ngram_size=2)
# Decode the model's output to text
feedback = tokenizer.decode(outputs[0], skip_special_tokens=True)
return feedback
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