| ---
|
| language:
|
| - th
|
| license: mit
|
| tags:
|
| - thai
|
| - nlp
|
| - ner
|
| - sentiment-analysis
|
| - question-answering
|
| - multi-task
|
| - transformer
|
| - pytorch
|
| - custom-model
|
| datasets:
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| - pythainlp/thainer-corpus-v2.2
|
| - pythainlp/wisesight_sentiment
|
| - iapp_wiki_qa_squad
|
| pipeline_tag: token-classification
|
| ---
|
|
|
| # 🇹🇭 Thai NLP Toolkit
|
|
|
| A **multi-task NLP framework** for the Thai language built from scratch with PyTorch.
|
|
|
| Uses a shared Transformer encoder backbone with three task-specific heads:
|
|
|
| | Task | Head | Metric |
|
| |------|------|--------|
|
| | **Named Entity Recognition** | Token classification (7 labels) | Entity-level F1 |
|
| | **Sentiment Analysis** | Sentence classification (3 labels) | Macro-F1 |
|
| | **Question Answering** | Extractive span prediction | EM / F1 |
|
|
|
| ## Model Architecture
|
|
|
| - **Tokenizer**: SentencePiece BPE (32K vocab) with Thai-specific preprocessing
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| - **Encoder**: 6-layer Transformer (d_model=256, 8 heads, d_ff=1024)
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| - **Max sequence length**: 512 tokens
|
|
|
| ## Usage
|
|
|
| ```python
|
| # Clone the repository first
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| # git clone https://github.com/puttibenz/thai-nlp-toolkit.git
|
|
|
| from inference.pipeline import ThaiNLPPipeline
|
|
|
| pipeline = ThaiNLPPipeline(model_dir="path/to/downloaded/model", device="auto")
|
|
|
| # NER
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| result = pipeline.predict("สมชายทำงานที่กรุงเทพ", task="ner")
|
|
|
| # Sentiment Analysis
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| result = pipeline.predict("อาหารอร่อยมากครับ", task="sentiment")
|
|
|
| # Question Answering
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| result = pipeline.predict(
|
| "กรุงเทพมหานครเป็นเมืองหลวงของประเทศไทย",
|
| task="qa",
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| question="เมืองหลวงของประเทศไทยคืออะไร"
|
| )
|
| ```
|
|
|
| ## Training Data
|
|
|
| | Dataset | Task | Source |
|
| |---------|------|--------|
|
| | ThaiNER v2.2 | NER | `pythainlp/thainer-corpus-v2.2` |
|
| | Wisesight Sentiment | Sentiment | `pythainlp/wisesight_sentiment` |
|
| | iApp Thai Wiki QA | QA | `iapp_wiki_qa_squad` |
|
|
|
| ## Training Details
|
|
|
| - **Framework**: PyTorch (custom implementation)
|
| - **Training**: Multi-task learning with round-robin sampling
|
| - **Optimizer**: AdamW with cosine LR schedule + warmup
|
| - **Mixed Precision**: FP16 on CUDA
|
| - **Batch Size**: 32 (×4 gradient accumulation = effective 128)
|
|
|
| ## File Structure
|
|
|
| ```
|
| thai-nlp-toolkit/
|
| ├── checkpoint.pt # Model weights
|
| ├── config.yaml # Model architecture config
|
| └── tokenizer/
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| ├── thai_bpe.model # SentencePiece BPE model
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| └── tokenizer_config.json # Tokenizer config
|
| ```
|
|
|
| ## Source Code
|
|
|
| GitHub: [puttibenz/thai-nlp-toolkit](https://github.com/puttibenz/thai-nlp-toolkit)
|
|
|
| ## License
|
|
|
| MIT
|
|
|
