ExeGen Qwen2.5-14B v2 — QLoRA (2021-expanded)
QLoRA adapter for exegetical generation (terse Sanskrit → expansive English commentary), fine-tuned on the expanded ExeGen train set.
- Base: Qwen/Qwen2.5-14B-Instruct (4-bit nf4, QLoRA r=16, α=32, 3 epochs)
- Train: 1,594 pairs (704 original + 890 new verse→oral-commentary pairs from Mark Dyczkowski's 2021 Tantrāloka ch5/7/8/9/10 lectures), vs the v1 adapter's 704.
- Trained on Brev (7×H100 DDP, ~9 min) — successor to
exegen-qwen14b-lora.
Usage
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-14B-Instruct", device_map="auto")
model = PeftModel.from_pretrained(base, "Anamavajra-Labs/exegen-qwen14b-v2-lora")
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