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base_model: mistralai/Mistral-7B-Instruct-v0.2
library_name: peft
pipeline_tag: text-generation
tags:
- peft
- qlora
- qualitative-research
- open-coding
---
# mistral7b QLoRA Open-Coding Adapter
This PEFT adapter fine-tunes `mistralai/Mistral-7B-Instruct-v0.2` to produce exactly one concise open code
for an input utterance or qualitative text segment.
## Output schema
Task mode: `single_code`.
```json
{"code": "short analytical label"}
```
## Held-out verification
- Rows: 100
- Valid JSON rate: 1.000
- Non-empty rate: 1.000
- Exact set match: 0.200
- Mean set F1: 0.200
- 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.
## Loading
```python
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2")
tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2")
model = PeftModel.from_pretrained(base_model, "Likich/open-coding-mistral7b-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.
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