Update README.md

README.md

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 ---
+language:
+- tr
+- en
+- de
+- es
+- fr
+- ru
+- zh
+- ja
+- ko
+license: mit
+tags:
+- turkish
+- türkiye
+- ai
+- lamapi
+- next
+- next-x1
+- text-generation
+- open-source
+- 70b
+- large-language-model
+- llm
+- transformer
+- artificial-intelligence
+- machine-learning
+- nlp
+- multilingual
+- instruction-tuned
+- chat
+- generative-ai
+- optimized
+- trl
+- sft
+- enterprise
+- industrial
+pipeline_tag: text-generation
+datasets:
+- mlabonne/FineTome-100k
+- Gryphe/ChatGPT-4o-Writing-Prompts
+- uclanlp/Brief-Pro
 library_name: transformers
-tags: []
 ---
 
-# Model Card for Model ID
+![70b](https://cdn-uploads.huggingface.co/production/uploads/67d46bc5fe6ad6f6511d6f44/017hoTVIfgFInU5ZUVQjv.png)
 
-<!-- Provide a quick summary of what the model is/does. -->
+# 🚀 Next 70B (ultra1295)
 
+### *Türkiye’s Most Powerful AI — Industrial Scale, High Precision, and Enterprise-Ready*
 
+[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)
+[![Language: Multilingual](https://img.shields.io/badge/Language-Multilingual-red.svg)]()
+[![HuggingFace](https://img.shields.io/badge/🤗-Lamapi/Next--70B-orange.svg)](https://huggingface.co/Lamapi/next-70b)
 
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
-
-## Training Details
-
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
+---
 
-### Results
+## 📖 Overview
 
-[More Information Needed]
+**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.
 
-#### Summary
+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
 
-## Model Examination [optional]
+- 🇹🇷 **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.
 
-<!-- Relevant interpretability work for the model goes here -->
+---
 
-[More Information Needed]
+## 📊 Benchmark Performance
 
-## Environmental Impact
+**Next 70B** demonstrates world-class performance, surpassing major competitors in key academic and industrial benchmarks.
 
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+![WhatsApp Image 2025-11-29 at 15.37.04_764ee845](https://cdn-uploads.huggingface.co/production/uploads/67d46bc5fe6ad6f6511d6f44/OEZUOh78lc0q0vJm3dlVh.jpeg)
 
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+---
 
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
+## 🚀 Installation & Usage
 
-## Technical Specifications [optional]
+**Note:** We recommend using a multi-GPU setup (e.g., 2x A100 80GB) for full precision or 48GB+ VRAM for 4-bit quantization.
 
-### Model Architecture and Objective
+```
+!pip install unsloth
+```
 
-[More Information Needed]
+```python
+from unsloth import FastLanguageModel
 
-### Compute Infrastructure
+model, tokenizer = FastLanguageModel.from_pretrained("Lamapi/next-70b")
 
-[More Information Needed]
+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
+)
 
-#### Hardware
+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),
+)
+```
 
-[More Information Needed]
+---
 
-#### Software
+## 🧩 Key Features
 
-[More Information Needed]
+| 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.              |
 
-## Citation [optional]
+---
 
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+## 📐 Model Specifications
 
-**BibTeX:**
+| 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                 |
 
-[More Information Needed]
+---
 
-**APA:**
+## 🎯 Ideal Use Cases
 
-[More Information Needed]
+* **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
 
-## Glossary [optional]
+---
 
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+## 📄 License
 
-[More Information Needed]
+Licensed under the **MIT License** — free for commercial and non-commercial use. Attribution is appreciated.
 
-## More Information [optional]
+---
 
-[More Information Needed]
+## 📞 Contact & Support
 
-## Model Card Authors [optional]
+* 📧 **Email:** [lamapicontact@gmail.com](mailto:lamapicontact@gmail.com)
+* 🤗 **HuggingFace:** [Lamapi](https://huggingface.co/Lamapi)
 
-[More Information Needed]
+---
 
-## Model Card Contact
+> **Next 70B** — Türkiye’s flagship AI model. Built for those who demand **accuracy**, **speed**, and **scale**.
 
-[More Information Needed]
+[![Follow on HuggingFace](https://img.shields.io/badge/Follow-HuggingFace-yellow?logo=huggingface)](https://huggingface.co/Lamapi)