Nanthasit/sakthai-combined-v7

SakThai Combined v7

 

Curated, larger-scale instruction-tuning data for tool-calling, function-calling, and agent-style reasoning in the SakThai model family.

Dataset Summary

SakThai Combined v7 extends the v6 family with more multi-turn examples, broader tool coverage, and stronger <tool>/function-calling formatting. It is intended for fine-tuning models that should invoke tools naturally, then continue the conversation after tool results.

Data Fields

Dataset Structure

• —Config: default
• —Train split: present
• —Test split: present
• —Format: JSONL
• —Language: English, with multilingual assistant turns preserved from source conversations

Splits

Dataset Size

Verified Snapshot

Loading Examples

from datasets import load_dataset

ds = load_dataset("Nanthasit/sakthai-combined-v7")
print(ds)

from datasets import load_dataset

ds = load_dataset("Nanthasit/sakthai-combined-v7", split="train")
example = ds[0]
print(example["messages"])
print(example["tools"][0]["function"]["name"])

from datasets import load_dataset

# inspect test split only
test = load_dataset("Nanthasit/sakthai-combined-v7", split="test")
print(f"Test examples: {len(test)}")
print(test[0]["messages"][-1]["content"])

Streaming / Partial Load

from datasets import load_dataset

ds = load_dataset("Nanthasit/sakthai-combined-v7", split="train", streaming=True)
for i, row in enumerate(ds):
    if i >= 1:
        break
    print(row["tools"][0]["function"]["name"])

Dataset Creation

• —Curation: Combined from prior SakThai combined datasets with additional tool-calling and multi-turn coverage.
• —Annotation: examples include expected tool-call formatting and assistant follow-up behavior.
• —Scope: training and evaluation for tool-use instruction tuning.

Use Cases

• —Fine-tuning instruction-following models for function-calling.
• —Evaluating tool-calling format adherence on held-out tools.
• —Agent-style multi-turn conversation training with tool results.

Citation

@misc{sakthai-combined-v7,
  title={SakThai Combined v7},
  author={Beer / Nanthasit},
  year={2026},
  url={https://huggingface.co/datasets/Nanthasit/sakthai-combined-v7
}

Evaluation & Community

Results are surfaced in the SakThai Leaderboard.

License

CC BY 4.0

Part of the SakThai Model Family.