---
language:
- en
license: llama3.2
library_name: transformers
base_model:
- meta-llama/Llama-3.2-1B-Instruct
- Llama-3.2-SUN-2.5B-chat
datasets:
- 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
pipeline_tag: text-generation

---

# MedIT SUN 1B

<div align="center">
  <img src="https://i.ibb.co/PF0TdMJ/imagine-image-9a56cee7-0f4f-4cc2-b265-a5b8d04f266b.png" alt="Llama-3.2-MedIT-SUN-2.5B" style="border-radius: 10px; box-shadow: 0 4px 8px 0 rgba(0, 0, 0, 0.2), 0 6px 20px 0 rgba(0, 0, 0, 0.19); max-width: 100%; height: auto;">
</div>

**Base Model**
- Llama 3.2 1B -> MedIT SUN 2.5B -> MedIT SUN 1B

**Mesh Size**
- 1B to 2.5B parameters [MedIT SUN 2.5B](https://huggingface.co/meditsolutions/Llama-3.2-SUN-2.5B-chat) -> 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: chat-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

**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