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jsantillana/qwen2.5-3b-f1-strategy-lora (the paper's post-race
strategy-explanation model, fine-tuned on a different prompt/format). This adapter is
fine-tuned specifically on the prompt/context format used by
services/api/commentary.py::build_context and SYSTEM_PROMPT/PROMPTS, so it learns to
terminate cleanly after 2-3 sentences instead of degenerating into repetition.1from peft import PeftModel
2from transformers import AutoModelForCausalLM, AutoTokenizer
3base = "Qwen/Qwen2.5-3B-Instruct"
4tok = AutoTokenizer.from_pretrained(base)
5model = AutoModelForCausalLM.from_pretrained(base, torch_dtype="auto", device_map="auto")
6model = PeftModel.from_pretrained(model, "jsantillana/qwen2.5-3b-f1-commentary-lora")strategy_sim/track_store.state_at_lap) paired
with the exact commentary.py prompt and a deterministic grounded template
(commentary._template_text) as the target. 2025/2026 seasons held out for eval.