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<action>...</action> tags.Qwen/Qwen3-0.6B. First, LoRA SFT is performed on successful DeepSeek-V4-Flash ALFWorld trajectories converted to step-level samples with full factual Observation/Action history. The resulting checkpoint is then full-parameter fine-tuned on additional successful pick_cool_then_place_in_recep and pick_two_obj_and_place demonstrations collected with a 50-step horizon.| Pick | Look | Clean | Heat | Cool | Pick2 | All |
|---|---|---|---|---|---|---|
| 94.29 +/- 2.86 | 76.92 +/- 0.00 | 77.78 +/- 0.00 | 50.00 +/- 0.00 | 84.00 +/- 0.00 | 70.83 +/- 4.17 | 78.57 +/- 0.00 |
1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model_id = "qiangwhu/Qwen3-0.6B-ALFWorld-FullHistory-SFT"
4tokenizer = AutoTokenizer.from_pretrained(model_id)
5model = AutoModelForCausalLM.from_pretrained(model_id, dtype="bfloat16")