70b

🚀 Next 70B (ultra1295)

Türkiye’s Most Powerful AI — Industrial Scale, High Precision, and Enterprise-Ready

License: MIT Language: Multilingual HuggingFace


📖 Overview

Next 70B is a state-of-the-art 70-billion parameter large language model (LLM) engineered for maximum accuracy, versatility, and instruction following. Built upon an optimized transformer architecture, it delivers SOTA performance across coding, mathematics, and creative writing tasks.

As the flagship model of the series, Next 70B is designed to handle the most demanding enterprise workloads. It excels at nuanced language understanding in Turkish and English, complex data processing, and generating production-grade code, making it a superior alternative to proprietary models.


⚡ Highlights

  • 🇹🇷 Türkiye’s most powerful open-weights AI model
  • 🏆 Top-tier Performance: Beats GPT-5.1 in MATH (99.0%) and achieves near-perfect GSM8K scores.
  • 🌍 Master-level multilingual understanding (Turkish, English, and 30+ languages)
  • 💻 Coding Specialist: Exceptional Python and JavaScript generation capabilities (HumanEval 97.8%).
  • 🏢 Industrial-grade stability for critical infrastructure
  • 📝 Precise Instruction Following: High IFEval score (95.0) ensures strict adherence to formatting and constraints.

📊 Benchmark Performance

Next 70B demonstrates world-class performance, surpassing major competitors in key academic and industrial benchmarks.

WhatsApp Image 2025-11-29 at 15.37.04_764ee845


🚀 Installation & Usage

Note: We recommend using a multi-GPU setup (e.g., 2x A100 80GB) for full precision or 48GB+ VRAM for 4-bit quantization.

!pip install unsloth
from unsloth import FastLanguageModel

model, tokenizer = FastLanguageModel.from_pretrained("Lamapi/next-70b")

messages = [
    {"role": "system", "content": "You are Next-X1, a helpful, smart, and precise AI assistant created by Lamapi."},
    {"role" : "user", "content" : "Write a Python script to optimize a neural network using PyTorch."}
]
text = tokenizer.apply_chat_template(
    messages,
    tokenize = False,
    add_generation_prompt = True
)

from transformers import TextStreamer
_ = model.generate(
    **tokenizer(text, return_tensors = "pt").to("cuda"),
    max_new_tokens = 2048,
    temperature = 0.7, top_p = 0.95, top_k = 400,
    streamer = TextStreamer(tokenizer, skip_prompt = True),
)

🧩 Key Features

Feature Description
📚 Massive Knowledge Base Trained on a diverse, high-quality dataset covering science, history, and law.
🇹🇷 Cultural Mastery Native-level nuance in Turkish idioms and professional terminology.
⚙️ High-Performance Scaling Optimized for high-throughput inference and low latency.
🧮 Scientific & Coding Excellence 99.0% MATH score. Solves complex engineering and algorithmic problems.
🎯 Precision Focused Designed for tasks requiring strict output formats and high factual accuracy.
🏢 Enterprise Reliability Consistent and safe outputs suitable for commercial applications.

📐 Model Specifications

Specification Details
Base Model Llama
Parameters 70 Billion
Architecture Transformer (Causal LLM)
Modalities Text-only
Fine-Tuning SFT & DPO on high-quality instruct datasets
Optimizations GQA, Flash Attention 3, Quantization-ready
Primary Focus General Purpose Assistant, Math, Multilingual Chat

🎯 Ideal Use Cases

  • Enterprise Assistants — Customer support and internal knowledge management
  • Advanced Code Generation — Full-stack development and debugging
  • Content Creation — High-quality marketing copy, emails, and reports
  • Translation & Localization — Highly accurate translation between Turkish/English
  • Data Extraction — Structuring unstructured data into JSON/SQL
  • Academic Assistance — Solving math problems and summarizing research papers

📄 License

Licensed under the MIT License — free for commercial and non-commercial use. Attribution is appreciated.


📞 Contact & Support


Next 70B — Türkiye’s flagship AI model. Built for those who demand accuracy, speed, and scale.

Follow on HuggingFace

Downloads last month
9
Safetensors
Model size
71B params
Tensor type
F16
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 3 Ask for provider support

Datasets used to train Lamapi/next-70b

Collection including Lamapi/next-70b