Likich/open-coding-qwen25_7b-single_code-qlora

qwen25_7b QLoRA Open-Coding Adapter

This PEFT adapter fine-tunes Qwen/Qwen2.5-7B-Instruct to produce exactly one concise open code for an input utterance or qualitative text segment.

Output schema

Task mode: single_code.

{"code": "short analytical label"}

Held-out verification

• —Rows: 100
• —Valid JSON rate: 1.000
• —Non-empty rate: 1.000
• —Exact set match: 0.160
• —Mean set F1: 0.160
• —Average generated codes: 1.000
• —Verification passed: True

Exact match is reported as a format and regression diagnostic, not as a complete measure of open-code quality. Valid abstractive labels may differ in wording.

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from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer

base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-7B-Instruct")
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-7B-Instruct")
model = PeftModel.from_pretrained(base_model, "Likich/open-coding-qwen25_7b-single_code-qlora")

The repository contains adapter weights, tokenizer metadata, training metadata, held-out verification metrics, and sample predictions. It does not contain the full base-model weights.