language, license, library_name, base_model, datasets, pipeline_tag, model-index

language	license	library_name	base_model	datasets	pipeline_tag	model-index
en	llama3.2	transformers	meta-llama/Llama-3.2-1B-Instruct Llama-3.2-SUN-2.5B-chat	argilla/OpenHermesPreferences argilla/magpie-ultra-v0.1 argilla/Capybara-Preferences-Filtered mlabonne/open-perfectblend HuggingFaceTB/everyday-conversations-llama3.1-2k WizardLMTeam/WizardLM_evol_instruct_V2_196k ProlificAI/social-reasoning-rlhf allenai/tulu-3-sft-mixture allenai/llama-3.1-tulu-3-8b-preference-mixture	text-generation	name results Llama-3.2-SUN-1B-Instruct 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 64.13 strict accuracy url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-1B-Instruct 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 9.18 normalized accuracy url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-1B-Instruct 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 4.61 exact match url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-1B-Instruct 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 0.0 acc_norm url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-1B-Instruct 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 4.05 acc_norm url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-1B-Instruct 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 8.68 accuracy url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-1B-Instruct Open LLM Leaderboard

MedIT SUN 1B Instruct

Base Model

• Llama 3.2 1B -> MedIT SUN 2.5B -> MedIT SUN 1B -> Knowledge Injection from Llama 3.1 8B Instruct

Mesh Size

• 1B to 2.5B parameters MedIT SUN 2.5B -> layers mesh using MedIT-mesh technique and downscaled to 1B

Extension Method

• Proprietary technique developed by MedIT Solutions

Fine-tuning

• Open (or open subsets allowing for commercial use) open datasets from HF
• Open (or open subsets allowing for commercial use) SFT datasets from HF

Training Status

• Current version: instruct-1.0.0

Key Features

• Built on Llama 3.2 architecture
• Upscaled from 1B to 2.47B parameters
• Optimized for open-ended conversations
• Incorporates supervised fine-tuning for improved performance
• Layers meshing using the MedIT-mesh technique
• Downscaled to 1B
• Knowledge injection from Llama 3.1 8B Instruct using new technique developed by MedIT Solutions

Use Case

• General conversation and task-oriented interactions

Limitations As the model is still in training, performance and capabilities may vary. Users should be aware that the model is not in its final form and may exhibit inconsistencies or limitations typical of in-progress AI models.

Disclaimer and Safety Considerations The Model is designed to be used as a smart assistant but not as a knowledge source within your applications, systems, or environments. It is not intended to provide 100% accurate answers, especially in scenarios where high precision and accuracy are

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	15.11
IFEval (0-Shot)	64.13
BBH (3-Shot)	9.18
MATH Lvl 5 (4-Shot)	4.61
GPQA (0-shot)	0.00
MuSR (0-shot)	4.05
MMLU-PRO (5-shot)	8.68