next-8b / README.md
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metadata
language:
  - tr
  - en
  - de
  - es
  - fr
  - ru
  - zh
  - ja
  - ko
license: mit
tags:
  - turkish
  - türkiye
  - reasoning
  - ai
  - lamapi
  - gemma3
  - next
  - next-x1
  - text-generation
  - open-source
  - 14b
  - large-language-model
  - llm
  - transformer
  - artificial-intelligence
  - machine-learning
  - nlp
  - multilingual
  - instruction-tuned
  - chat
  - generative-ai
  - optimized
  - trl
  - sft
  - cognitive
  - analytical
  - enterprise
pipeline_tag: text-generation
datasets:
  - CognitiveKernel/CognitiveKernel-Pro-SFT
  - OpenSPG/KAG-Thinker-training-dataset
  - QuixiAI/dolphin-r1
  - uclanlp/Brief-Pro
  - Gryphe/Opus-WritingPrompts
  - GreenerPastures/All-Your-Base-Full
  - dongguanting/ARPO-SFT-54K
  - Medint/Multi-Med-conversational
  - mlabonne/smoltalk-flat
  - mlabonne/natural_reasoning-formatted
  - QuixiAI/open-instruct-uncensored
  - mlabonne/open-perfectblend
library_name: transformers

🧠 Next 8B (m427)

Türkiye’s Compact Reasoning AI — Logical, Analytical, and Efficient

License: MIT Language: Multilingual HuggingFace


📖 Overview

Next 8B is an 8-billion parameter large language model (LLM) built on Qwen 3 architecture, optimized for reasoning and analytical performance. It’s Türkiye’s reasoning-capable compact AI, designed to think, infer, and solve problems efficiently.

Focused purely on cognitive tasks, it excels in problem-solving, abstract logic, and multilingual understanding (Turkish, English, and more).


⚡ Highlights

  • 🇹🇷 Türkiye’s compact reasoning AI
  • 🧠 Logical, analytical, and inferential reasoning
  • 🌍 Multilingual support (Turkish, English, 30+ languages)
  • Lightweight and efficient
  • 💬 Instruction-tuned for dialogue, tutoring, and analysis

📊 Benchmark Performance

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
Next 8B (Thinking) 91.0 88.5 96.2 88.0
GPT-5 92.5 87.0 98.4 96.0
Claude Opus 4.1 (Thinking) ~92.0 87.8 84.7 95.4

🚀 Installation & Usage

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "Lamapi/next-8b"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")

messages = [
    {"role": "system", "content": "You are Next-X1, a reasoning-capable AI assistant created by Lamapi. You think logically, reason efficiently, and answer concisely."},
    {"role": "user", "content": "Explain why the sky appears blue using logical reasoning."}
]

prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

outputs = model.generate(**inputs, max_new_tokens=150)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

🧩 Key Features

Feature Description
🧠 Efficient Reasoning Strong in abstract logic, critical thinking, and structured problem-solving.
🇹🇷 Multilingual Intelligence Deep Turkish understanding with 30+ language support.
Lightweight & Optimized Quantized formats (Q8_0, Q4_K_M, FP16) for efficiency.
🧮 Mathematical & Analytical Skill Handles structured reasoning and moderate complexity problems.
🧩 Non-Vision Architecture Focused on text-based cognitive tasks.
🏢 Reliable & Consistent Predictable outputs suitable for professional use.

📐 Model Specifications

Specification Details
Base Model Qwen 3
Parameters 8 Billion
Architecture Transformer (Causal LLM)
Modalities Text-only
Fine-Tuning Instruction-tuned with reasoning datasets
Optimizations Quantization-ready, FP16 support
Primary Focus Reasoning, logic, decision-making, and language understanding

🎯 Ideal Use Cases

  • Compact Analytical Chatbots
  • Research Assistance (scientific/legal)
  • Education & Tutoring
  • Code & Algorithm Design
  • Decision Support Systems

💡 Performance Highlights

  • Efficient Reasoning: Compact yet powerful logical reasoning.
  • Good Mathematical Understanding: Handles structured problems reliably.
  • Lightweight & Fast: Ideal for resource-conscious environments.
  • Consistent Outputs: Professional-grade reliability in smaller footprint.

📄 License

Licensed under MIT License — free for commercial and non-commercial use.


📞 Contact & Support


Next 8B — compact reasoning-capable AI, blending logical depth, analytical efficiency, and lightweight reliability.

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