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thelamapi/next-70b-GGUF
next-70b-GGUF is a text generation model from thelamapi. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
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From the Hugging Face model README

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

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),
)
| Feature | Description |
|---|---|
| ๐ Massive Knowledge Base | Trained on a diverse, high-quality dataset covering science, history, and law. |
| ๐น๐ท Cultural Mastery | Native-level nuance in Turkish idioms and professional terminology. |
| โ๏ธ High-Performance Scaling | Optimized for high-throughput inference and low latency. |
| ๐งฎ Scientific & Coding Excellence | 99.0% MATH score. Solves complex engineering and algorithmic problems. |
| ๐ฏ Precision Focused | Designed for tasks requiring strict output formats and high factual accuracy. |
| ๐ข Enterprise Reliability | Consistent and safe outputs suitable for commercial applications. |
| 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 |
Licensed under the MIT License โ free for commercial and non-commercial use. Attribution is appreciated.
Next 70B โ Tรผrkiyeโs flagship AI model. Built for those who demand accuracy, speed, and scale.