初始化项目，由ModelHub XC社区提供模型
Model: NeuronUz/NeuronAI-Uzbek Source: Original Platform
This commit is contained in:
ModelHub XC
270
README.md
Normal file
270
README.md
Normal file
@@ -0,0 +1,270 @@
|
||||
---
|
||||
language:
|
||||
- uz
|
||||
- en
|
||||
license: apache-2.0
|
||||
base_model: Qwen/Qwen3-4B
|
||||
tags:
|
||||
- uzbek
|
||||
- qwen3
|
||||
- language-model
|
||||
- text-generation
|
||||
- nlp
|
||||
- central-asia
|
||||
- low-resource
|
||||
- tokenizer-optimization
|
||||
datasets:
|
||||
- behbudiy/alpaca-cleaned-uz
|
||||
- NeuronUz/uzbek-spelling-mcq
|
||||
pipeline_tag: text-generation
|
||||
model-index:
|
||||
- name: NeuronAI-Uzbek
|
||||
results:
|
||||
- task:
|
||||
type: text-generation
|
||||
name: Uzbek Language Understanding
|
||||
dataset:
|
||||
name: UzLiB Benchmark
|
||||
type: uzlib
|
||||
metrics:
|
||||
- type: accuracy
|
||||
value: 0.662
|
||||
name: Overall Accuracy
|
||||
---
|
||||
|
||||
<div align="center">
|
||||
|
||||
# 🇺🇿 NeuronAI-Uzbek
|
||||
|
||||
### The Most Advanced Open-Source Language Model for Uzbek
|
||||
|
||||
[](https://huggingface.co/NeuronUz/NeuronAI-Uzbek)
|
||||
[](https://opensource.org/licenses/Apache-2.0)
|
||||
[](https://huggingface.co/Qwen/Qwen3-4B)
|
||||
|
||||
**🏆 4th Place Globally | 🥇 1st Place in Uzbekistan on UzLiB Benchmark**
|
||||
|
||||
*Outperforming GPT-4o, Claude 3.5 Sonnet, and Gemini 2.5 Flash on Uzbek language tasks*
|
||||
|
||||
</div>
|
||||
|
||||
---
|
||||
|
||||
## 📊 Key Results
|
||||
|
||||
<div align="center">
|
||||
|
||||
| Achievement | Value |
|
||||
|-------------|-------|
|
||||
| **UzLiB Overall Score** | **0.662** |
|
||||
| **Global Ranking** | **#4** |
|
||||
| **Regional Ranking** | **#1 in Uzbekistan** |
|
||||
| **Tokenizer Efficiency Improvement** | **+22.5%** vs Qwen3-4B |
|
||||
|
||||
</div>
|
||||
|
||||
---
|
||||
|
||||
## 🏆 UzLiB Benchmark Performance
|
||||
|
||||
NeuronAI-Uzbek achieves exceptional performance on the [UzLiB Benchmark](https://github.com/tahrirchi/uzlib/blob/main/LEADERBOARD.md), the comprehensive evaluation suite for Uzbek language understanding.
|
||||
|
||||
### Leaderboard Position
|
||||
|
||||
[](https://github.com/tahrirchi/uzlib/blob/main/LEADERBOARD.md)
|
||||
|
||||
|
||||
> **Note**: NeuronAI-Uzbek is the **smallest model** in the top 10, with only **4B parameters**, while competing against models with 100B+ parameters.
|
||||
|
||||
### Performance Comparison vs Original Qwen3-4B
|
||||
|
||||
| Metric | Qwen3-4B (Original) | NeuronAI-Uzbek | Improvement |
|
||||
|--------|:-------------------:|:--------------:|:-----------:|
|
||||
| **Overall (All)** | 0.345 | **0.662** | **+91.9%** |
|
||||
| Correct Word | 0.351 | 0.718 | +104.6% |
|
||||
| Meaning | 0.309 | 0.466 | +50.8% |
|
||||
| Meaning in Context | 0.347 | 0.333 | -4.0% |
|
||||
| Fill-in | 0.327 | 0.385 | +17.7% |
|
||||
|
||||
---
|
||||
|
||||
## 🔤 Tokenizer Efficiency
|
||||
|
||||
We optimized the tokenizer specifically for Uzbek, achieving significantly better tokenization efficiency (lower fertility rate = fewer tokens per word = faster inference and lower costs).
|
||||
|
||||
### Fertility Rate Comparison
|
||||
|
||||
| Model | Fertility Rate | Std Dev | Vocab Size | Improvement vs Qwen3 |
|
||||
|-------|:--------------:|:-------:|:----------:|:--------------------:|
|
||||
| **NeuronAI-Uzbek (Ours)** 🏆 | **2.67** | 0.15 | 180,000 | **+22.5%** |
|
||||
| Gemma 2-9B | 3.15 | 0.22 | 256,000 | +8.3% |
|
||||
| LLaMA 3.1-8B | 3.32 | 0.22 | 128,256 | +3.7% |
|
||||
| DeepSeek-V3 | 3.32 | 0.21 | 128,815 | +3.4% |
|
||||
| Qwen3-4B (Original) | 3.44 | 0.22 | 151,669 | - |
|
||||
|
||||
> **Fertility Rate**: Average number of tokens per word. Lower is better for efficiency.
|
||||
|
||||
<div align="center">
|
||||
<img src="assets/fertility_comparison_chart.png" alt="Tokenizer Fertility Rate Comparison" width="700"/>
|
||||
</div>
|
||||
|
||||
### What This Means
|
||||
|
||||
- **22.5% fewer tokens** needed to represent Uzbek text
|
||||
- **Faster inference** due to shorter sequences
|
||||
- **Lower API costs** when deployed
|
||||
- **Better context utilization** - fit more content in the same context window
|
||||
|
||||
---
|
||||
|
||||
## 🛠️ Model Details
|
||||
|
||||
### Architecture
|
||||
|
||||
| Property | Value |
|
||||
|----------|-------|
|
||||
| **Base Model** | Qwen3-4B |
|
||||
| **Parameters** | 4 Billion |
|
||||
| **Vocabulary Size** | 180,000 tokens |
|
||||
| **Context Length** | 32,768 tokens |
|
||||
| **Architecture** | Transformer (Decoder-only) |
|
||||
| **Precision** | BFloat16 |
|
||||
|
||||
### Training Methodology
|
||||
|
||||
1. **Tokenizer Surgery**: Extended vocabulary with 40,000 Uzbek-optimized tokens
|
||||
2. **Embedding Initialization**: Semantic initialization using subword composition
|
||||
3. **Continual Pretraining**: Trained on 2B tokens of Uzbek and English text corpus
|
||||
4. **Instruction Fine-tuning**: Aligned using Uzbek and English instruction datasets
|
||||
|
||||
### Training Data
|
||||
|
||||
| Dataset | Type | Purpose |
|
||||
|---------|------|---------|
|
||||
| Uzbek Web Corpus | Pretraining | Language modeling |
|
||||
| behbudiy/alpaca-cleaned-uz | SFT | Uzbek instructions |
|
||||
| NeuronUz/uzbek-spelling-mcq | SFT | Benchmark-targeted training |
|
||||
| vicgalle/alpaca-gpt4 | SFT | English capability retention |
|
||||
|
||||
---
|
||||
|
||||
## 🚀 Quick Start
|
||||
|
||||
### Installation
|
||||
|
||||
```bash
|
||||
pip install transformers torch
|
||||
```
|
||||
|
||||
### Basic Usage
|
||||
|
||||
```python
|
||||
from transformers import AutoModelForCausalLM, AutoTokenizer
|
||||
|
||||
model_name = "NeuronUz/NeuronAI-Uzbek"
|
||||
|
||||
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
|
||||
model = AutoModelForCausalLM.from_pretrained(
|
||||
model_name,
|
||||
torch_dtype="auto",
|
||||
device_map="auto",
|
||||
trust_remote_code=True
|
||||
)
|
||||
|
||||
prompt = "O'zbekiston haqida qisqacha ma'lumot bering."
|
||||
|
||||
messages = [
|
||||
{"role": "user", "content": prompt}
|
||||
]
|
||||
|
||||
text = tokenizer.apply_chat_template(
|
||||
messages,
|
||||
tokenize=False,
|
||||
add_generation_prompt=True
|
||||
)
|
||||
|
||||
inputs = tokenizer(text, return_tensors="pt").to(model.device)
|
||||
outputs = model.generate(
|
||||
**inputs,
|
||||
max_new_tokens=512,
|
||||
temperature=0.7,
|
||||
top_p=0.9,
|
||||
do_sample=True
|
||||
)
|
||||
|
||||
response = tokenizer.decode(outputs[0][inputs['input_ids'].shape[1]:], skip_special_tokens=True)
|
||||
print(response)
|
||||
```
|
||||
|
||||
### With Thinking Mode (Chain-of-Thought)
|
||||
|
||||
```python
|
||||
messages = [
|
||||
{"role": "user", "content": "5 ta 3 ga bo'linuvchi 100 dan kichik natural sonlarni toping."}
|
||||
]
|
||||
|
||||
text = tokenizer.apply_chat_template(
|
||||
messages,
|
||||
tokenize=False,
|
||||
add_generation_prompt=True,
|
||||
enable_thinking=True # Enable step-by-step reasoning
|
||||
)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 📈 Use Cases
|
||||
|
||||
NeuronAI-Uzbek excels at:
|
||||
|
||||
- **📝 Text Generation**: Creative writing, content creation in Uzbek
|
||||
- **❓ Question Answering**: Answering questions about Uzbek culture, history, and general knowledge
|
||||
- **📚 Reading Comprehension**: Understanding and analyzing Uzbek texts
|
||||
- **🔤 Grammar & Spelling**: Uzbek language correctness tasks
|
||||
- **🌐 Translation Assistance**: Uzbek-English language tasks
|
||||
- **💬 Conversational AI**: Building Uzbek chatbots and assistants
|
||||
|
||||
---
|
||||
|
||||
## ⚠️ Limitations
|
||||
|
||||
- **Knowledge Cutoff**: Training data has a knowledge cutoff date
|
||||
- **Hallucinations**: May generate plausible-sounding but incorrect information
|
||||
- **Bias**: May reflect biases present in training data
|
||||
- **Not for Critical Applications**: Should not be used for medical, legal, or safety-critical applications without human oversight
|
||||
|
||||
---
|
||||
|
||||
## 📜 License
|
||||
|
||||
This model is released under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0).
|
||||
|
||||
---
|
||||
|
||||
## 🙏 Acknowledgments
|
||||
|
||||
- **Qwen Team** at Alibaba for the excellent Qwen3-4B base model
|
||||
- **UzLiB Benchmark** creators for the comprehensive evaluation framework
|
||||
- **Uzbek NLP Community** for datasets and linguistic resources
|
||||
|
||||
---
|
||||
|
||||
## 📖 Citation
|
||||
|
||||
```bibtex
|
||||
@misc{neuronai-uzbek-2025,
|
||||
title={NeuronAI-Uzbek: An Optimized Language Model for Uzbek},
|
||||
author={NeuronAI Team},
|
||||
year={2025},
|
||||
publisher={Hugging Face},
|
||||
url={https://huggingface.co/NeuronUz/NeuronAI-Uzbek}
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
<div align="center">
|
||||
|
||||
**Built with ❤️ in Uzbekistan by [NeuronUz](https://huggingface.co/NeuronUz)**
|
||||
|
||||
</div>
|
||||
Reference in New Issue
Block a user