Instructions to use Maxwe11y/qwen3-ala-adapters with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Maxwe11y/qwen3-ala-adapters with PEFT:
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- Notebooks
- Google Colab
- Kaggle
Qwen3 ALA LoRA Adapters
This repository contains LoRA adapters trained from Qwen/Qwen3-8B for
controlled research on verb-centric counterfactual logic adaptation. Base-model
weights and training data are not included.
Included Adapters
| Directory | Configuration |
|---|---|
output-qwen3-auto-g5-64-3-1e-05-3-token-25-uni |
Standard SFT, n=3 |
output-qwen3-auto-g5-64-3-1e-05-1.0-0.1-3-token-25-uni |
Contrastive-only, alpha=0.1, n=3 |
output-qwen3-sft-g5-0.05-64-3-1e-05-3-token-25-uni |
Adaptive-only, beta=0.05, n=3 |
output-qwen3-contrastive-g5-0.1-0.1-64-3-1e-05-1.0-0.5-3-token-25-uni |
Contrastive adaptation, beta=0.1, alpha=0.5, n=3 |
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from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = "Qwen/Qwen3-8B"
adapter = "Maxwe11y/qwen3-ala-adapters/output-qwen3-contrastive-g5-0.1-0.1-64-3-1e-05-1.0-0.5-3-token-25-uni"
tokenizer = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(base, device_map="auto")
model = PeftModel.from_pretrained(model, adapter)
Use these adapters only for controlled research and evaluation.
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