Datasets:
Tasks:
Text Generation
Languages:
English
Size:
n<1K
Tags:
code
notebooks
training-scripts
dataset:Nanthasit/sakthai-kaggle-notebooks
license-mit
dataset-card
License:
Update dataset card with enhanced documentation
Browse files
README.md
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<div align="center">
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[](https://huggingface.co/datasets/Nanthasit/sakthai-kaggle-notebooks)
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| Attribute | Value |
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|-----------|-------|
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| Files | **16** (15 files +
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| Total size | **~141 KB** |
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| Created | 2026-07-06 |
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| Last updated | 2026-07-30 |
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| Downloads | **184** |
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| License | Apache 2.0 |
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| Repository type | Dataset (notebook & script collection) |
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| Format | `.py` (PEP 723), `.ipynb` (Jupyter)
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---
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## Data Fields
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This dataset is a **collection of Python scripts and Jupyter notebooks**, not a tabular dataset. Each file is a self-contained artifact with
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| Field | Type | Description |
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|-------|------|-------------|
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| `size` | `integer` | File size in KB |
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| `type` | `string` | Category: `training-notebook`, `training-script`, `eval-script`, `validation-script`, `deployment-script`, `infra` |
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| `model_target` | `string` | Target model size: `0.5B`, `1.5B`, `7B`, or `all` |
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| `purpose` | `string` | One-sentence description of the file's role |
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| `era` | `string` | Pipeline generation: `v6-era`, `v7-era`, or `infra` |
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| `dependencies` | `string` | Key Python package dependencies (e.g., `transformers`, `trl`, `peft`, `huggingface_hub`) |
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```python
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from datasets import load_dataset
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# Load the dataset (returns a Dataset with file
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ds = load_dataset("Nanthasit/sakthai-kaggle-notebooks", split="train")
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print(ds)
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# Dataset({
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# features: ['filename', 'path', 'size', 'type'],
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# num_rows: 16
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# })
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```
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### List all available files
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```python
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from huggingface_hub import HfApi
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print(f"Downloaded to: {script_path}")
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```
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### Run a training job (PEP 723)
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```bash
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# All job scripts are PEP 723 inline-script compatible
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cd /tmp
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curl -
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uv run job-0.5b-v7.py
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```
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### Open notebooks in Kaggle
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```bash
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curl -
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# Then upload to Kaggle via kaggle kernels push
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```
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---
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##
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[sakthai-combined-
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## License
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<div align="center">
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[](https://huggingface.co/datasets/Nanthasit/sakthai-kaggle-notebooks)
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[](https://huggingface.co/datasets/Nanthasit/sakthai-kaggle-notebooks)
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| Attribute | Value |
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|-----------|-------|
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| Files | **16** (15 data files + `README.md` + `.gitattributes`) |
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| Total size | **~141 KB** |
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| Created | 2026-07-06 |
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| Last updated | 2026-07-30 |
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| Downloads | **184** |
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| License | Apache 2.0 |
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| Repository type | Dataset (notebook & script collection) |
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| Format | `.py` (PEP 723 inline-script), `.ipynb` (Jupyter notebook) |
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---
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## Data Fields
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This dataset is a **collection of Python scripts and Jupyter notebooks**, not a tabular dataset. Each file is a self-contained artifact with the following attributes:
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| Field | Type | Description |
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|-------|------|-------------|
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| `size` | `integer` | File size in KB |
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| `type` | `string` | Category: `training-notebook`, `training-script`, `eval-script`, `validation-script`, `deployment-script`, `infra` |
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| `model_target` | `string` | Target model size: `0.5B`, `1.5B`, `7B`, or `all` |
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| `purpose` | `string` | One-sentence description of the file's role in the pipeline |
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| `era` | `string` | Pipeline generation: `v6-era`, `v7-era`, or `infra` |
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| `dependencies` | `string` | Key Python package dependencies (e.g., `transformers`, `trl`, `peft`, `huggingface_hub`) |
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```python
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from datasets import load_dataset
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# Load the dataset (returns a Dataset with file metadata)
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ds = load_dataset("Nanthasit/sakthai-kaggle-notebooks", split="train")
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print(ds)
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# Dataset({
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# features: ['filename', 'path', 'size', 'type', 'model_target', 'purpose', 'era', 'dependencies'],
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# num_rows: 16
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# })
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# List all filenames in the collection
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for row in ds:
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print(f"{row['filename']:40s} {row['type']:20s} {row['model_target']:6s} {row['era']}")
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```
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### List all available files via HfApi
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```python
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from huggingface_hub import HfApi
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print(f"Downloaded to: {script_path}")
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```
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### Run a training job (PEP 723 inline-script)
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```bash
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# All job scripts are PEP 723 inline-script compatible
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cd /tmp
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curl -OL https://huggingface.co/datasets/Nanthasit/sakthai-kaggle-notebooks/raw/main/job-0.5b-v7.py
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uv run job-0.5b-v7.py
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```
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### Open notebooks in Kaggle
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```bash
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curl -OL https://huggingface.co/datasets/Nanthasit/sakthai-kaggle-notebooks/raw/main/sakthai-engine.ipynb
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# Then upload to Kaggle via kaggle kernels push
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```
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---
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## File Inventory
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| # | File | Type | Size |
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|---|------|------|------|
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| 1 | `sakthai-engine.ipynb` | Training notebook (1.5B) | 10.5 KB |
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| 2 | `sakthai-7b-engine.ipynb` | Training notebook (7B) | 24.0 KB |
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| 3 | `train-sakthai-0.5b-v2.py` | Training script (0.5B, v6) | 6.8 KB |
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| 4 | `job-0.5b-v7.py` | Training script (0.5B, v7) | 10.2 KB |
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| 5 | `job-0.5b-hfjobs.py` | Training script (0.5B, HF Jobs) | 7.8 KB |
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| 6 | `job-0.5b-exp.py` | Experimental script (0.5B) | 12.9 KB |
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| 7 | `job-0.5b-nanguard.py` | Ablation: nan guard | 13.2 KB |
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| 8 | `job-0.5b-nanhunt.py` | Ablation: nan hunt | 11.8 KB |
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| 9 | `scripts/train-sakthai-1.5b-v2.py` | Training script (1.5B) | 4.5 KB |
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| 10 | `scripts/sakthai-7b-post-train.py` | Post-training (7B) | 13.7 KB |
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| 11 | `eval-bfcl-0.5b.py` | BFCL evaluation | 3.9 KB |
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| 12 | `validate.py` | Validation script | 4.9 KB |
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| 13 | `validate_exp.py` | Experimental validation | 3.7 KB |
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| 14 | `deploy-endpoint.py` | Deploy to HF Endpoints | 3.1 KB |
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| 15 | `.gitattributes` | Git LFS config | 2.4 KB |
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| 16 | `README.md` | This dataset card | ~7 KB |
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---
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## Related Datasets & Models
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| Asset | Description |
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|-------|-------------|
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| [Nanthasit/sakthai-combined-v6](https://huggingface.co/datasets/Nanthasit/sakthai-combined-v6) | Base training data (v6 generation) |
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| [Nanthasit/sakthai-combined-v7](https://huggingface.co/datasets/Nanthasit/sakthai-combined-v7) | Extended training data (v7 generation) |
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| [Nanthasit/sakthai-bench-v1](https://huggingface.co/datasets/Nanthasit/sakthai-bench-v1) | Benchmark holdout data |
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| [Nanthasit/sakthai-tool-calling-v1](https://huggingface.co/datasets/Nanthasit/sakthai-tool-calling-v1) | Tool-calling training data (SimpleToolCalling) |
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| 🤖 [SakThai Agents](https://huggingface.co/Nanthasit) | All models in the House of Sak |
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| 🏠 [SakThai Model Family](https://huggingface.co/collections/Nanthasit/sakthai-model-family-6a64745450b12d421c1f9f02) | Complete model family collection |
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---
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<div align="center">
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<sub>Built with ❤️ by Beer · Part of the <a href="https://huggingface.co/Nanthasit">House of Sak</a> — one family, one home.</sub>
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</div>
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