# 🚀 Next-1B (t416) ### *Lightweight, Efficient, and Türkiye-Focused AI* [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT) [![Language: English](https://img.shields.io/badge/Language-Multilingual-red.svg)]() [![HuggingFace](https://img.shields.io/badge/🤗-Lamapi/Next--1B-orange.svg)](https://huggingface.co/Lamapi/next-1b) --- ## 📖 Overview **Next-1B** is a **1-billion parameter causal language model** based on **Gemma 3**, designed for **efficiency, low-resource deployment, and reasoning-focused natural language understanding**. Key highlights: * Extremely **lightweight** — can run on consumer GPUs with low VRAM. * Optimized for **text reasoning, summarization, and creative generation**. * Supports **Turkish natively** while remaining multilingual. * Open-source and transparent for research and applications. Ideal for **developers, students, and organizations** needing **fast, reliable, and low-resource text-generation**. --- # Our Next 1B and Next 4B models are leading to all of the tiny models in benchmarks.

Model	MMLU (5-shot) %	MMLU-Pro %	GSM8K %	MATH %
Next 4B preview	84.6	66.9	82.7	70.5
Next 1B Version t327	87.3	69.2	90.5	70.1
Qwen 3 0.6B	52.81	37.6	60.7	20.5
Llama 3.2 1B	49.3	44.4	11.9	30.6

--- # Also, our Next 14b model is leading to state-of-the-art models in some of the Benchmarks.

Model	MMLU (5-shot) %	MMLU-Pro %	GSM8K %	MATH %
Next 14B (Thinking)	94.6	93.2	98.8	92.7
Next 12B	92.7	84.4	95.3	87.2
GPT-5	92.5	87.0	98.4	96.0
Claude Opus 4.1 (Thinking)	~92.0	87.8	84.7	95.4

--- ## 🎯 Goals 1. **Lightweight Efficiency:** Run smoothly on low-resource devices. 2. **Reasoning-Focused:** Provide logical and coherent text outputs. 3. **Accessibility:** Fully open-source with clear documentation. 4. **Multilingual Adaptability:** Turkish-focused but supports other languages. --- ## ✨ Key Features | Feature | Description | | --------------------------- | --------------------------------------------------------------------- | | 🔋 Lightweight Architecture | Optimized for low VRAM usage; ideal for small GPUs or CPU deployment. | | 🇹🇷 Turkish & Multilingual | Handles complex Turkish prompts accurately. | | 🧠 Reasoning Capabilities | Logical chain-of-thought for question-answering and problem-solving. | | 📊 Consistent Outputs | Reliable and reproducible results across multiple runs. | | 🌍 Open Source | Transparent, research-friendly, and community-driven. | --- ## 📐 Model Specifications | Specification | Details | | ------------------ | ---------------------------------------------------------------------- | | Base Model | Gemma 3 | | Parameter Count | 1 Billion | | Architecture | Transformer, causal LLM | | Fine-Tuning Method | Instruction fine-tuning (SFT) with Turkish and multilingual datasets | | Optimizations | Quantization-ready (q8, f16, f32) | | Use Cases | Text generation, summarization, Q&A, creative writing, reasoning tasks | --- ## 🚀 Installation & Usage ### Use the model: ```python from transformers import AutoTokenizer, AutoModelForCausalLM import torch model_id = "Lamapi/next-1b" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained(model_id) # Chat message messages = [ {"role": "system", "content": "You are Next-X1, a smart and concise AI assistant trained by Lamapi. Always respond in the user's language. Proudly made in Turkey."}, {"role": "user", "content": "Hello, how are you?"} ] # Prepare input with Tokenizer prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) inputs = tokenizer(prompt, return_tensors="pt") # Output from the model output = model.generate(**inputs, max_new_tokens=50) print(tokenizer.decode(output[0], skip_special_tokens=True)) ```

Hello, how are you?

I'm fine, thank you. How are you?

--- ## 📄 License MIT License — free to use, modify, and distribute. Attribution appreciated. --- ## 📞 Contact & Support * 📧 **Email:** [lamapicontact@gmail.com](mailto:lamapicontact@gmail.com) * 🤗 **HuggingFace:** [Lamapi](https://huggingface.co/Lamapi) --- > **Next-1B** — Lightweight, **efficient, and reasoning-focused**, bringing **Turkey’s AI forward** on low-resource hardware. [![Follow on HuggingFace](https://img.shields.io/badge/Follow-HuggingFace-yellow?logo=huggingface)](https://huggingface.co/Lamapi)