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Amouri28
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Model Details
Model Provider
Amouri28
Model Tree
Qwen/Qwen3-4B-Instruct-2507
Input Modalities
Output Modalities
Supported Functionality
This adapter is trained to improve structured output accuracy (JSON / YAML / XML / TOML / CSV).
Loss is applied only to the final assistant output, while intermediate reasoning (Chain-of-Thought) is masked.
python
from transformers import AutoModelForCausalLM, AutoTokenizerfrom peft import PeftModelimport torch base = "Qwen/Qwen3-4B-Instruct-2507"adapter = "your_id/your-repo" tokenizer = AutoTokenizer.from_pretrained(base)model = AutoModelForCausalLM.from_pretrained( base, torch_dtype=torch.float16, device_map="auto",)model = PeftModel.from_pretrained(model, adapter)Training data: daichira/structeval-t-sft-hq-yaml-cleaned
Dataset License: MIT License. This dataset is used and distributed under the terms of the MIT License. Compliance: Users must comply with the MIT license (including copyright notice) and the base model's original terms of use.