File size: 2,343 Bytes
fcefdea | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 | """The model card's example: two steps of the questioner on a two-hop question."""
import re
import torch
from huggingface_hub import hf_hub_download
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
REPO = "dolev31/ProactiveInquirer-Qwen3-8B"
tok = AutoTokenizer.from_pretrained("Qwen/Qwen3-8B")
model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-8B", dtype=torch.bfloat16, device_map="auto")
model = PeftModel.from_pretrained(model, REPO) # seed 1; add subfolder="seed2" for the second seed
template = open(hf_hub_download(REPO, "prompts/inquirer_prompted.txt"), encoding="utf-8").read()
placebo = open(hf_hub_download(REPO, "prompts/fragment_user_channel_placebo.txt"), encoding="utf-8").read()
def next_action(**state):
fields = dict(state, user_channel=placebo.strip())
prompt = re.sub(r"\{\{(\w+)\}\}", lambda m: str(fields[m.group(1)]), template)
ids = tok.apply_chat_template(
[{"role": "user", "content": prompt}],
add_generation_prompt=True,
enable_thinking=False,
return_tensors="pt",
return_dict=True,
).to(model.device)
out = model.generate(**ids, max_new_tokens=200, do_sample=False)
return tok.decode(out[0, ids["input_ids"].shape[1] :], skip_special_tokens=True)
question = "Who was the spouse of the director of the film The Great Flamarion?"
instructions = (
"Answer the question using a closed pool of 20 paragraphs. You may issue retrieval "
"queries against that pool before answering; several paragraphs are distractors, and "
"the answer usually requires composing facts from more than one of them."
)
print(next_action(
question=question, instructions=instructions, evidence="(nothing retrieved yet)",
draft="(no draft yet)", history="(nothing asked yet)",
))
evidence = (
"[3f2a9c1b7d4e] The Great Flamarion\n"
"The Great Flamarion is a 1945 American film noir directed by Anthony Mann and starring "
"Erich von Stroheim, Mary Beth Hughes and Dan Duryea."
)
print(next_action(
question=question, instructions=instructions, evidence=evidence,
draft="The film was directed by Anthony Mann; his spouse is not yet known.",
history="Q1: Who directed the film The Great Flamarion?\n"
"A1: The Great Flamarion (1945) was directed by Anthony Mann.",
))
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