Instructions to use dementor-research/sft_chatbot_arena_gemma-4-e4b_as_nemotron-nano-30b-a3b_seed42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dementor-research/sft_chatbot_arena_gemma-4-e4b_as_nemotron-nano-30b-a3b_seed42 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-4-E4B-it") model = PeftModel.from_pretrained(base_model, "dementor-research/sft_chatbot_arena_gemma-4-e4b_as_nemotron-nano-30b-a3b_seed42") - Notebooks
- Google Colab
- Kaggle
File size: 862 Bytes
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library_name: peft
tags:
- dementor
- imitation-disguise
- lora
- chatbot_arena
base_model: google/gemma-4-E4B-it
---
# sft_chatbot_arena_gemma-4-e4b_as_nemotron-nano-30b-a3b_seed42
CURRENT Dementor imitation (disguise) LoRA adapter — dataset **chatbot_arena**, **seed 42**.
- **Method:** SFT
- **Source model (fine-tuned / disguised):** `gemma-4-e4b` (base: `google/gemma-4-E4B-it`)
- **Target model being imitated:** `nemotron-nano-30b-a3b`
- **Dataset:** chatbot_arena (benign) | **Seed:** 42
This adapter trains the source model to imitate the target model's style on the benign
chatbot_arena corpus. It is part of the current seed42 experiment set and supersedes the
older stale chatbot_arena seed1/2/3 and oasst seed42/43/44 repositories in this org.
Registry key == repo id == `sft_chatbot_arena_gemma-4-e4b_as_nemotron-nano-30b-a3b_seed42`.
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