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dementor-research/
dpo_writingprompts_nemotron-nano-30b-a3b_as_granite-4-h-small_seed42

Name: dpo_writingprompts_nemotron-nano-30b-a3b_as_granite-4-h-small_seed42
Availability: InStock

nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16

adapter

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dpo_writingprompts_nemotron-nano-30b-a3b_as_granite-4-h-small_seed42

LoRA adapter trained via Tinker as part of the dementor configuration-defined behavioral-imitation study.

Base model: nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16
Training stage: DPO (LoRA rank 32, target_modules=all-linear)
Alias: dpo_writingprompts_nemotron-nano-30b-a3b_as_granite-4-h-small_seed42

Usage

python

from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer

base = AutoModelForCausalLM.from_pretrained("nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16")
tok = AutoTokenizer.from_pretrained("nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16")
model = PeftModel.from_pretrained(base, "dementor-research/dpo_writingprompts_nemotron-nano-30b-a3b_as_granite-4-h-small_seed42")

The named campaign contains 12 models, 4 datasets, and 1 seed(s), yielding 528 configured cells for this stage. See config.yaml in the code release for the exact cohort and hyperparameters.