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Published
20 hours ago •
jmikedupont2
jmikedupont2
test user ticket
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import torch from transformers import GPT2LMHeadModel, GPT2Tokenizer
class AutoGPTAgent: def init(self): self.commands = { "generate": self.generate_text, # Add more commands as needed } self.tokenizer = GPT2Tokenizer.from_pretrained("gpt2") self.model = GPT2LMHeadModel.from_pretrained("gpt2")
def generate_text(self, args):
# Join the arguments into a single string
prompt = " ".join(args)
# Encode the prompt and generate the text
inputs = self.tokenizer.encode(prompt, return_tensors="pt")
outputs = self.model.generate(inputs, max_length=100, temperature=0.7)
# Decode the generated text and print it
generated_text = self.tokenizer.decode(outputs[0])
print(generated_text)
def process_command(self, command, args):
if command in self.commands:
self.commandscommand
else:
print(f"Unknown command: {command}")
Usage:
agent = AutoGPTAgent() agent.process_command("generate", ["Hello, world!"])
