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- Apache 2.0 License - Zen Research DAO under Zoo Labs Inc (501(c)(3)) - San Francisco-based non-profit for open AI research - Copyright 2025 Zen Research Authors
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
#!/usr/bin/env python3.13
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"""Test agent identity"""
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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model = AutoModelForCausalLM.from_pretrained(
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"/Users/z/work/zen/zen-eco/agent/finetuned",
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torch_dtype=torch.float16,
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device_map="auto",
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trust_remote_code=True
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)
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tokenizer = AutoTokenizer.from_pretrained(
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"/Users/z/work/zen/zen-eco/agent/finetuned",
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trust_remote_code=True
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)
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prompts = ["Who are you?", "What model are you?", "What are your capabilities?"]
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for prompt in prompts:
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text = f"<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n"
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inputs = tokenizer(text, return_tensors="pt")
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inputs = {k: v.to(model.device) for k, v in inputs.items()}
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with torch.no_grad():
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outputs = model.generate(
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**inputs,
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max_new_tokens=50,
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temperature=0.1,
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do_sample=False,
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pad_token_id=tokenizer.eos_token_id
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)
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response = tokenizer.decode(outputs[0], skip_special_tokens=False)
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print(f"Q: {prompt}")
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print(f"A: {response.split('assistant')[-1].strip()}")
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print() |