Update README.md
Browse files
README.md
CHANGED
|
@@ -8,4 +8,86 @@ tags:
|
|
| 8 |
- aze
|
| 9 |
- mini
|
| 10 |
- yusiko
|
| 11 |
-
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 8 |
- aze
|
| 9 |
- mini
|
| 10 |
- yusiko
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
|
| 14 |
+
# π§ YouAI β Azerbaijani Language Model
|
| 15 |
+
**A lightweight, efficient, and fully custom Azerbaijani language model designed for text generation, chat applications, education, and research.**
|
| 16 |
+
YouAI is trained from scratch using a custom 10M-sample Azerbaijani dataset and optimized for running on consumer GPUs while maintaining competitive performance.
|
| 17 |
+
|
| 18 |
+
## π Features
|
| 19 |
+
- π¦πΏ Native Azerbaijani language support
|
| 20 |
+
- β‘ Lightweight architecture (β 36M parameter)
|
| 21 |
+
- π Supports fast inference with GGUF + llama.cpp
|
| 22 |
+
- π¦ Available on Hugging Face
|
| 23 |
+
- π― Optimized for chatbots, WebRTC real-time assistants, and low-latency deployment
|
| 24 |
+
|
| 25 |
+
## ποΈ Model Architecture
|
| 26 |
+
| Version | Parameters | Type | Context Length | Notes |
|
| 27 |
+
|--------|------------|------|----------------|-------|
|
| 28 |
+
| YouAI-36M | ~36.6M | GPT-2 Small variant | 1024 | Higher quality |
|
| 29 |
+
|
| 30 |
+
Architecture:
|
| 31 |
+
- Transformer decoder-only
|
| 32 |
+
- Multi-head self-attention
|
| 33 |
+
- Rotary positional embeddings (RoPE)
|
| 34 |
+
- GELU activation
|
| 35 |
+
- Layer normalization
|
| 36 |
+
- Tied embeddings
|
| 37 |
+
|
| 38 |
+
## π Dataset
|
| 39 |
+
YouAI is trained on a 10 million-sample Azerbaijani dataset including:
|
| 40 |
+
- News, books, conversations, social media, web articles, educational content
|
| 41 |
+
|
| 42 |
+
Preprocessing:
|
| 43 |
+
- Unicode normalization, deduplication, tokenizer preprocessing, length filtering
|
| 44 |
+
|
| 45 |
+
## ποΈ Training Details
|
| 46 |
+
### Hardware
|
| 47 |
+
- NVIDIA RTX 3090 24GB
|
| 48 |
+
- PyTorch 2.x + CUDA 12
|
| 49 |
+
- bf16 mixed precision
|
| 50 |
+
|
| 51 |
+
### Hyperparameters
|
| 52 |
+
```
|
| 53 |
+
epochs = 1
|
| 54 |
+
batch_size = 32
|
| 55 |
+
gradient_accumulation = 4
|
| 56 |
+
learning_rate = 3e-4
|
| 57 |
+
warmup_steps = 500
|
| 58 |
+
weight_decay = 0.1
|
| 59 |
+
sequence_length = 512
|
| 60 |
+
optimizer = AdamW
|
| 61 |
+
precision = bf16
|
| 62 |
+
```
|
| 63 |
+
|
| 64 |
+
## π Training Challenges & Solutions
|
| 65 |
+
### Bottleneck: Memory Bandwidth
|
| 66 |
+
Small models saturate VRAM bandwidth β ~4.2 it/s
|
| 67 |
+
Solution: shrink model size, adjust batch/accumulation, optimize data loading
|
| 68 |
+
|
| 69 |
+
### Transformers
|
| 70 |
+
```python
|
| 71 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer
|
| 72 |
+
tok = AutoTokenizer.from_pretrained("Yusiko/YouAI")
|
| 73 |
+
model = AutoModelForCausalLM.from_pretrained("Yusiko/YouAI")
|
| 74 |
+
```
|
| 75 |
+
|
| 76 |
+
## π Hugging Face
|
| 77 |
+
Available at: https://huggingface.co/Yusiko/YouAI
|
| 78 |
+
|
| 79 |
+
## π¦ License
|
| 80 |
+
GPL 3.0 License
|
| 81 |
+
|
| 82 |
+
## π Future Plans
|
| 83 |
+
- 1B+ model
|
| 84 |
+
- Better tokenizer
|
| 85 |
+
- Instruction-tuning
|
| 86 |
+
- WebGPU inference
|
| 87 |
+
- Community fine-tuning tools
|
| 88 |
+
|
| 89 |
+
## π€ Contact
|
| 90 |
+
Created by **Yusiko**
|
| 91 |
+
GitHub: Yusiko99[https://github.com/Yusiko99]
|
| 92 |
+
Website: https://yusi.xo.je
|
| 93 |
+
Hugging Face: Yusiko
|