GPT 3.5

GPT.py

from transformers import GPTNeoForCausalLM, GPT2Tokenizer

# Initialize tokenizer and model
tokenizer = GPT2Tokenizer.from_pretrained("EleutherAI/gpt-neo-2.7B")
model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt-neo-2.7B")

# Example usage
text = "Replace with your input text here."

# Tokenize input text
inputs = tokenizer(text, return_tensors="pt")

# Generate output
with tokenizer.as_target_tokenizer():
    outputs = model.generate(**inputs, max_length=100, num_return_sequences=1)

# Decode output tokens to text
output_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

# Print or use the generated text
print("Input Text:", text)
print("Generated Text:", output_text)