library_name, model-index, license, language, base_model

library_name	model-index	license	language	base_model
transformers	name results ldm_soup_Llama-3.1-8B-Inst task dataset metrics source type name text-generation Text Generation name type args IFEval (0-Shot) HuggingFaceH4/ifeval num_few_shot 0 type value name inst_level_strict_acc and prompt_level_strict_acc 80.33 strict accuracy url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type args BBH (3-Shot) BBH num_few_shot 3 type value name acc_norm 31.1 normalized accuracy url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type args MATH Lvl 5 (4-Shot) hendrycks/competition_math num_few_shot 4 type value name exact_match 11.56 exact match url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type args GPQA (0-shot) Idavidrein/gpqa num_few_shot 0 type value name acc_norm 5.26 acc_norm url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type args MuSR (0-shot) TAUR-Lab/MuSR num_few_shot 0 type value name acc_norm 11.52 acc_norm url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args MMLU-PRO (5-shot) TIGER-Lab/MMLU-Pro main test num_few_shot 5 type value name acc 32.07 accuracy url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst Open LLM Leaderboard	apache-2.0	en	meta-llama/Llama-3.1-8B-Instruct

Model Card for DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in

• compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0

Overview

DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst is developed by deepAuto.ai and builds upon the VAGOsolutions/Llama-3.1-SauerkrautLM-8B-Instruct model. Our approach leverages the base model’s pretrained weights and optimizes them for the Winogrande and ARC-Challenge datasets by training a latent diffusion model on the pretrained weights.

Through this process, we learn the distribution of the base model's weight space, enabling us to explore optimal configurations. We then sample multiple sets of weights, using the model-soup averaging technique to identify the best-performing weights for both datasets. These weights are merged using linear interpolation to create the final model weights for DeepAutoAI/ldm_soup_Llama-3.1-8B-Inst.

This approach has led to improved performance on previously unseen leaderboard tasks, all without any additional task-specific training.

The work is currently in progress

References

Diffusion-Based Neural Network Weights Generation

Evaluation

Results

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	28.64
IFEval (0-Shot)	80.33
BBH (3-Shot)	31.10
MATH Lvl 5 (4-Shot)	11.56
GPQA (0-shot)	5.26
MuSR (0-shot)	11.52
MMLU-PRO (5-shot)	32.07