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Update dataset card with enhanced documentation

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  1. README.md +49 -25
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@@ -18,6 +18,7 @@ datasets:
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  <div align="center">
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  [![Downloads](https://img.shields.io/badge/dynamic/json?url=https://huggingface.co/api/datasets/Nanthasit/sakthai-kaggle-notebooks&query=$.downloads&label=downloads&color=blue)](https://huggingface.co/datasets/Nanthasit/sakthai-kaggle-notebooks)
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  ![Last updated](https://img.shields.io/badge/updated-2026--07--30-green)
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  ![License](https://img.shields.io/badge/license-Apache%202.0-brightgreen)
@@ -35,20 +36,20 @@ datasets:
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  | Attribute | Value |
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  |-----------|-------|
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- | Files | **16** (15 files + 1 subdirectory `scripts/`) |
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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), `.gitattributes` |
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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 these attributes:
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  | Field | Type | Description |
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  |-------|------|-------------|
@@ -57,7 +58,7 @@ This dataset is a **collection of Python scripts and Jupyter notebooks**, not a
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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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@@ -150,16 +151,20 @@ This dataset is a **collection of Python scripts and Jupyter notebooks**, not a
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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 list)
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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
@@ -184,41 +189,60 @@ script_path = hf_hub_download(
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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 -O 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 -O 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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- ### Validate before training
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- ```bash
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- curl -O https://huggingface.co/datasets/Nanthasit/sakthai-kaggle-notebooks/raw/main/validate.py
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- uv run validate.py
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- ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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- ## What it builds
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- These notebooks train the full SakThai family from
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- [sakthai-combined-v6](https://huggingface.co/datasets/Nanthasit/sakthai-combined-v6) and
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- [sakthai-combined-v7](https://huggingface.co/datasets/Nanthasit/sakthai-combined-v7) —
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- the flagship [context-1.5b-merged](https://huggingface.co/Nanthasit/sakthai-context-1.5b-merged),
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- the 0.5B/7B variants, and the tool-calling LoRAs.
 
 
 
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- **17 models · 10 datasets · 3 Spaces** — [full collection →](https://huggingface.co/collections/Nanthasit/sakthai-model-family-6a64745450b12d421c1f9f02)
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-
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- ## License
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- Apache 2.0.
 
 
 
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  <div align="center">
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+ [![Dataset on HF](https://huggingface.co/datasets/Nanthasit/sakthai-kaggle-notebooks/badge.svg)](https://huggingface.co/datasets/Nanthasit/sakthai-kaggle-notebooks)
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  [![Downloads](https://img.shields.io/badge/dynamic/json?url=https://huggingface.co/api/datasets/Nanthasit/sakthai-kaggle-notebooks&query=$.downloads&label=downloads&color=blue)](https://huggingface.co/datasets/Nanthasit/sakthai-kaggle-notebooks)
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  ![Last updated](https://img.shields.io/badge/updated-2026--07--30-green)
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  ![License](https://img.shields.io/badge/license-Apache%202.0-brightgreen)
 
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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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+
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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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+
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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>