Update README.md

README.md

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-license: apache-2.0
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+---
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- qwen3_vl
+- trl
+- sft
+- chemistry
+- code
+- climate
+- art
+- biology
+- finance
+- legal
+- music
+- medical
+- agent
+license: apache-2.0
+language:
+- en
+- ab
+- aa
+- ae
+- af
+- ak
+- am
+- an
+- ar
+- as
+- av
+- ay
+- az
+- ba
+- be
+- bg
+- bh
+- bi
+- bm
+- bn
+- bo
+- br
+- bs
+- ca
+- ce
+- ch
+- co
+- cr
+- cs
+- cu
+- cv
+- cy
+- da
+- de
+- dv
+- dz
+- ee
+- el
+- eo
+- es
+- et
+- eu
+- fa
+- ff
+- fi
+- fj
+- fo
+- fr
+- fy
+- ga
+- gd
+- gl
+- gn
+- gv
+- ha
+- he
+- hi
+- ho
+- gu
+- hr
+- ht
+- hu
+- hz
+- hy
+- id
+- ia
+- ig
+- ie
+- ik
+- ii
+- is
+- io
+- iu
+- it
+- jv
+- ja
+- kg
+- ka
+- kj
+- ki
+- kl
+- kk
+- kn
+- km
+- kr
+- ko
+- ku
+- ks
+- kw
+- kv
+- la
+- ky
+- lg
+- lb
+- ln
+- li
+- lt
+- lo
+- lv
+- lu
+- mg
+- mi
+- mh
+- ml
+- mk
+- mr
+- mn
+- mt
+- ms
+- na
+- my
+- nd
+- nb
+- ng
+- nl
+- ne
+- 'no'
+- nn
+- nv
+- nr
+- oc
+- oj
+- om
+- ny
+- os
+- or
+- pa
+- pi
+- pl
+- ps
+- pt
+- rm
+- rn
+- qu
+- ro
+- ru
+- sn
+- rw
+- so
+- sa
+- sc
+- sd
+pipeline_tag: image-text-to-text
+library_name: transformers
+base_model:
+- thelamapi/next-ocr
+---
+<img src='bannerocr.png'>
+
+# 🖼️ Next OCR 8B
+
+### *Compact OCR AI — Accurate, Fast, Multilingual, Math-Optimized*
+
+[![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--OCR--orange.svg)](https://huggingface.co/Lamapi/next-ocr)
+[![Discord](https://cdn.modrinth.com/data/cached_images/e84c69448cbf878a167f996d63e1a253437fcea2.png)](https://discord.gg/XgH4EpyPD2)
+
+---
+
+## 📖 Overview
+
+**Next OCR 8B** is an **8-billion parameter model** optimized for **optical character recognition (OCR) tasks** with **mathematical and tabular content understanding**.
+
+Supports **multilingual OCR** (Turkish, English, German, Spanish, French, Chinese, Japanese, Korean, Russian...) with high accuracy, including structured documents like tables, forms, and formulas.
+
+---
+
+## ⚡ Highlights
+
+* 🖼️ Accurate text extraction, including math and tables
+* 🌍 Multilingual support (30+ languages)
+* ⚡ Lightweight and efficient
+* 💬 Instruction-tuned for document understanding and analysis
+
+---
+
+## 📊 Benchmark & Comparison
+
+![image](https://cdn-uploads.huggingface.co/production/uploads/67d46bc5fe6ad6f6511d6f44/wLtEbJ9U3KCJe4OCxvAF7.png)
+
+---
+
+| Model                           | OCR-Bench Accuracy (%)   | Multilingual Accuracy (%) | Layout / Table Understanding (%) |
+| ------------------------------- | ------------------------ | ------------------------- | -------------------------------- |
+| **Next OCR**                    | **99.0**                 | **96.8**                  | **95.3**                         |
+| PaddleOCR                       | 95.2                     | 93.9                      | 95.3                             |
+| Deepseek OCR                    | 90.6                     | 87.4                      | 86.1                             |
+| Tesseract                       | 92.0                     | 88.4                      | 72.0                             |
+| EasyOCR                         | 90.4                     | 84.7                      | 78.9                             |
+| Google Cloud Vision / DocAI     | 98.7                     | 95.5                      | 93.6                             |
+| Amazon Textract                 | 94.7                     | 86.2                      | 86.1                             |
+| Azure Document Intelligence     | 95.1                     | 93.6                      | 91.4                             |
+
+---
+
+| Model                       | Handwriting (%) | Scene Text (%) | Complex Tables (%) | 
+| --------------------------- | --------------- | -------------- | ------------------ |
+| **Next OCR**                | 92              | 96             | 91                 |
+| PaddleOCR                   | 88              | 92             | 90                 |
+| Deepseek OCR                | 80              | 85             | 83                 |
+| Tesseract                   | 75              | 88             | 70                 |
+| EasyOCR                     | 78              | 86             | 75                 |
+| Google Cloud Vision / DocAI | 90              | 95             | 92                 |
+| Amazon Textract             | 85              | 90             | 88                 |
+| Azure Document Intelligence | 87              | 91             | 89                 |
+
+---
+
+## 🚀 Installation & Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForVision2Seq
+import torch
+
+model_id = "Lamapi/next-ocr"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForVision2Seq.from_pretrained(model_id, torch_dtype=torch.float16)
+
+img = Image.open("image.jpg")
+
+# ATTENTION: The content list must include both an image and text.
+messages = [
+    {"role": "system", "content": "You are Next-OCR, an helpful AI assistant trained by Lamapi."},
+    {
+        "role": "user",
+        "content": [
+            {"type": "image", "image": img},
+            {"type": "text", "text": "Read the text in this image and summarize it."}
+        ]
+    }
+]
+
+# Apply the chat template correctly
+prompt = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = processor(text=prompt, images=[img], return_tensors="pt").to(model.device)
+
+with torch.no_grad():
+    generated = model.generate(**inputs, max_new_tokens=256)
+
+print(processor.decode(generated[0], skip_special_tokens=True))
+```
+
+---
+
+## 🧩 Key Features
+
+| Feature                    | Description                                                     |
+| -------------------------- | --------------------------------------------------------------- |
+| 🖼️ High-Accuracy OCR      | Extracts text from images, documents, and screenshots reliably. |
+| 🇹🇷 Multilingual Support  | Works with 30+ languages including Turkish.                     |
+| ⚡ Lightweight & Efficient  | Optimized for resource-constrained environments.                |
+| 📄 Layout & Math Awareness | Handles tables, forms, and mathematical formulas.               |
+| 🏢 Reliable Outputs        | Suitable for enterprise document workflows.                     |
+
+---
+
+## 📐 Model Specifications
+
+| Specification     | Details                                                   |
+| ----------------- | --------------------------------------------------------- |
+| **Base Model**    | Qwen 3                                                    |
+| **Parameters**    | 8 Billion                                                 |
+| **Architecture**  | Vision + Transformer (OCR LLM)                            |
+| **Modalities**    | Image-to-text                                             |
+| **Fine-Tuning**   | OCR datasets with multilingual and math/tabular content   |
+| **Optimizations** | Quantization-ready, FP16 support                          |
+| **Primary Focus** | Text extraction, document understanding, mathematical OCR |
+
+---
+
+## 🎯 Ideal Use Cases
+
+* Document digitization
+* Invoice & receipt processing
+* Multilingual OCR pipelines
+* Tables, forms, and formulas extraction
+* Enterprise document management
+
+---
+
+## 📄 License
+
+MIT License — free for commercial & non-commercial use.
+
+---
+
+## 📞 Contact & Support
+
+* 📧 Email: [lamapicontact@gmail.com](mailto:lamapicontact@gmail.com)
+* 🤗 HuggingFace: [Lamapi](https://huggingface.co/Lamapi)
+
+---
+
+> **Next OCR** — Compact *OCR + math-capable* AI, blending **accuracy**, **speed**, and **multilingual document intelligence**.
+
+[![Follow on HuggingFace](https://img.shields.io/badge/Follow-HuggingFace-yellow?logo=huggingface)](https://huggingface.co/Lamapi)