---
license: apache-2.0
datasets:
- Magpie-Align/Magpie-Pro-300K-Filtered
language:
- de
- en
base_model:
- unsloth/Llama-3.2-3B-bnb-4bit
pipeline_tag: text-generation
library_name: adapter-transformers
tags:
- efficient
- llama
- llama3
- gguf
- ollama
- instruction-finetuning
---
# Nomi 1.0-3b
## Introduction
Nomi-1.0 is a **refined mid-range Large Language Model** based on the **Llama-3.2-3B** architecture. It was specifically developed to outperform standard 3B models in **structured reporting**,
**markdown formatting**, and **Python coding**, making it an ideal assistant for local deployment on consumer hardware.
**It is the first Model of the Nomi-Series**
## 🌟 Key Features & Improvements
* **Architecture:** Llama-3.2-3B (Optimized for 8GB VRAM GPUs like RTX 4060).
* **Formatting Master:** Specifically trained to use H1, H2, tables, and bold text to make information instantly scannable.
* **Coding Proficiency:** Fine-tuned on the Magpie-Pro dataset to write cleaner Python code with built-in error handling (`try-except`).
* **Multilingual Support:** Excellent performance in both German and English.
* **Efficiency:** High-speed inference (~60+ tokens/sec) with a very low memory footprint.
---
## 🧠 Training Details
The goal of Nomi-1.0 was to create a "bridge" model that feels as smart as a 7B model but runs with the speed of a 3B model.
* **Base Model:** `unsloth/Llama-3.2-3B-Instruct-bnb-4bit`
* **Fine-tuning:** SFT (Supervised Fine-Tuning) using the **Magpie-Pro** dataset.
* **Training Tool:** **Unsloth** (for 4-bit optimized training).
* **Optimization:** High LoRA Rank (r=32) was used to ensure the model captures complex structural nuances.
---
## 📝 Prompt Template (ChatML/Llama-3.2)
For the best results in Ollama or LM Studio, use the following template:
```text
<|start_header_id|>system<|end_header_id|>
You are Nomi-1.0, a high-performance 3B model. You provide superior, structured, and deep responses. Always use Markdown for clarity.<|eot_id|>
<|start_header_id|>user<|end_header_id|>
{Your Question}<|eot_id|>
<|start_header_id|>assistant<|end_header_id|>
```
## 🛠️ Usage (Ollama)
1. **Download** the `Nomi-1.0.gguf`.
2. **Create a Modelfile** with the following content:
```text
FROM ./Nomi-1.0.gguf
PARAMETER temperature 0.6
SYSTEM "You are Nomi-1.0, a high-performance 3B model. You provide superior, structured, and deep responses. Always use Markdown for clarity."
```
3. **Run the following command in your terminal:**
```text
ollama create Nomi-1.0 -f Modelfile
```
## ⚠️ Limitations As a 3B parameter model, Nomi-1.0 is not a replacement for GPT-4 or large 70B models when it comes to deep world knowledge or complex mathematical reasoning. It is a specialized tool for speed, local privacy, and high-quality document structure.
