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ram-lexsi/aligntune-testrun-GBMPO

sourceHugging Faceupdated 29d agoView on Hugging Face
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<div align="center"> <table border="0" cellspacing="0" cellpadding="0" style="border: none; border-collapse: collapse;"> <tr> <td align="center" style="border: none; vertical-align: middle;"> <a href="https://lexsi.ai/"><img src="https://huggingface.co/ram-lexsi/aligntune-testrun-GBMPO/resolve/main/aligntunelogo.png" alt="Lexsi Labs" style="height: 60px;"/></a> </td> <td align="center" style="border: none; vertical-align: middle;"> <a href="https://github.com/Lexsi-Labs/aligntune"><img src="https://huggingface.co/ram-lexsi/aligntune-testrun-GBMPO/resolve/main/aligntunebanner.png" alt="AlignTune" style="height: 60px;"/></a> </td> </tr> </table> </div>

aligntune-testrun-GBMPO

Built using AlignTune — supports any open-source model, any algorithm, any backend (TRL / Unsloth / ES / etc).

Finetuned fromQwen/Qwen2.5-0.5B
Algorithmgbmpo
Backendtrl
Artifactadapter
Published2026-08-27 07:22 UTC

Usage

python
from peft import AutoPeftModelForCausalLM
from transformers import AutoTokenizer

model = AutoPeftModelForCausalLM.from_pretrained("ram-lexsi/aligntune-testrun-GBMPO")
tokenizer = AutoTokenizer.from_pretrained("ram-lexsi/aligntune-testrun-GBMPO")

This repo is a LoRA adapter. Load it on top of Qwen/Qwen2.5-0.5B (PEFT does that from adapter_config.json).