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giuliofrey/
mecha-nudges-models

Name: mecha-nudges-models
Availability: InStock

peft

safetensors

lora

sequence-classification

text-classification

meta-llama/Llama-3.1-8B-Instruct

adapter

mit

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LoRA Adapters — Mecha-nudges for Machines

LoRA adapters for the main experiment in "Mecha-nudges for Machines." Each adapter fine-tunes Meta-Llama-3.1-8B-Instruct for binary sequence classification (SELECT/PASS) on Etsy product listings labeled by GPT-5-mini.

Structure

Directory	Description
`before/`	Pre-ChatGPT listings (before Nov 30, 2022)
`before_null/`	Pre-ChatGPT listings, null model (empty text)
`after/`	Post-ChatGPT listings (after Nov 30, 2022)
`after_null/`	Post-ChatGPT listings, null model (empty text)

Each directory contains:

adapter_model.safetensors — LoRA weight matrices (~320 MB)
adapter_config.json — LoRA configuration

LoRA Configuration

Rank (r): 32
Alpha: 64
Dropout: 0.05
Target modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
Task: Sequence classification (2 labels)

Usage

python

from peft import AutoPeftModelForSequenceClassification
from transformers import AutoTokenizer

model = AutoPeftModelForSequenceClassification.from_pretrained("path/to/before")
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-8B-Instruct")

Training Details

Base model: Meta-Llama-3.1-8B-Instruct
Labels: GPT-5-mini (SELECT/PASS tokens)
Dataset: Medium (~500K listings), balanced
Variables: title, item_details
Epochs: 3
Learning rate: 2e-4
Seed: 42

giuliofrey/mecha-nudges-models