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at = Did the person ever reside in or visit the place prior to the document’s publication?; isAt = Is the person located at the place in the immediate temporal context of the document?.| Model | Parameters | DE at | DE isAt | EN at | EN isAt | FR at | FR isAt |
|---|---|---|---|---|---|---|---|
| Qwen3.5-2B | 1.9B | 0.61 | 0.59 | 0.62 | 0.71 | 0.52 | 0.59 |
| Qwen3.5-4B | 4.5B | 0.75 | 0.73 | 0.69 | 0.73 | 0.70 | 0.79 |
| Qwen3.5-9B | 9.3B | 0.73 | 0.75 | 0.72 | 0.84 | 0.72 | 0.80 |
1from transformers import AutoModelForCausalLM, AutoTokenizer
2from peft import PeftModel
3
4# "2B", "4B", or "9B"
5SIZE = "2B"
6
7base = AutoModelForCausalLM.from_pretrained(
8 f"Qwen/Qwen3.5-{SIZE}", dtype="bfloat16"
9)
10model = PeftModel.from_pretrained(
11 base, f"Shakibyzn/Qwen3.5-{SIZE}-clef-hipe2026"
12)
13tokenizer = AutoTokenizer.from_pretrained(
14 f"Shakibyzn/Qwen3.5-{SIZE}-clef-hipe2026"
15)