Instructions to use dementor-research/dpo_chatbot_arena_llama-3.1-8b_as_qwen3.5-4b_seed43 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dementor-research/dpo_chatbot_arena_llama-3.1-8b_as_qwen3.5-4b_seed43 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "dementor-research/dpo_chatbot_arena_llama-3.1-8b_as_qwen3.5-4b_seed43") - Notebooks
- Google Colab
- Kaggle
dpo_chatbot_arena_llama-3.1-8b_as_qwen3.5-4b_seed43
Dementor imitation (disguise) LoRA adapter — dataset chatbot_arena, seed 43.
- Method: DPO
- Source model (fine-tuned / disguised):
llama-3.1-8b(base:meta-llama/Llama-3.1-8B-Instruct) - Target model being imitated:
qwen3.5-4b - Dataset: chatbot_arena | Seed: 43
This adapter trains the source model to imitate the target model's style on the
chatbot_arena corpus. Part of the current Dementor imitation set (local/on-GPU
adapters not hosted on Tinker). Registry key == repo id == dpo_chatbot_arena_llama-3.1-8b_as_qwen3.5-4b_seed43.
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Model tree for dementor-research/dpo_chatbot_arena_llama-3.1-8b_as_qwen3.5-4b_seed43
Base model
meta-llama/Llama-3.1-8B Finetuned
meta-llama/Llama-3.1-8B-Instruct