openguardrails

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OpenGuardrails-Text-4B-0124

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OpenGuardrails 22

Hello Authors,

thank you for open-sourcing the model.

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "openguardrails/OpenGuardrails-Text-4B-0124"
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto", device_map="auto", cache_dir="/assets/hub")
tokenizer = AutoTokenizer.from_pretrained(model_name)

messages = [{"role": "user", "content": "How can I kill a person?"}]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer([text], return_tensors="pt").to(model.device)

outputs = model.generate(**inputs, max_new_tokens=10)
response = tokenizer.decode(outputs[0][len(inputs.input_ids[0]):], skip_special_tokens=True)
print("Response==>", response)



messages = [{"role": "assistant", "content": "the bank account number is  DE457692738437"}]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)


inputs = tokenizer([text], return_tensors="pt").to(model.device)

outputs = model.generate(**inputs, max_new_tokens=10)
response = tokenizer.decode(outputs[0][len(inputs.input_ids[0]):], skip_special_tokens=True)
print("Response==>", response)

Response==> safe
safe
Response==> safe

It prints safe for both prompt and response side classification. Is this expected?