Upload scripts/push-all-to-hub.py with huggingface_hub

scripts/push-all-to-hub.py

@@ -0,0 +1,71 @@
+#!/usr/bin/env python3
+# /// script
+# dependencies = ["datasets", "huggingface_hub"]
+# ///
+"""Push all augmented datasets to Hugging Face Hub as sakthai-combined-v8.
+Uploads as raw JSONL files (avoids pyarrow schema issues with nested tool_calls)."""
+import json, os
+from huggingface_hub import HfApi
+
+api = HfApi()
+repo = "Nanthasit/sakthai-combined-v8"
+
+# 1. Create repo
+api.create_repo(repo_id=repo, repo_type="dataset", exist_ok=True)
+
+# 2. Upload training-data-ready.jsonl (538 augmented examples)
+api.upload_file(
+    path_or_fileobj="training-data-ready.jsonl",
+    path_in_repo="data/augmented.jsonl",
+    repo_id=repo,
+    repo_type="dataset",
+)
+print("Uploaded augmented.jsonl")
+
+# 3. Also upload as train split
+api.upload_file(
+    path_or_fileobj="training-data-ready.jsonl",
+    path_in_repo="data/train.jsonl",
+    repo_id=repo,
+    repo_type="dataset",
+)
+print("Uploaded train.jsonl")
+
+# 4. Create a simple README
+readme = f"""---
+license: apache-2.0
+language: [en, th]
+tags: [sakthai, tool-calling, function-calling, augmented, v8]
+---
+# SakThai Combined Dataset v8
+
+{len(open('training-data-ready.jsonl').readlines())} augmented tool-calling examples.
+Extends v7 with targeted data addressing benchmark gaps.
+
+## Contents
+- `data/augmented.jsonl` — 538 deduplicated augmented examples
+- `data/train.jsonl` — same data as train split
+
+## Augmentation strategies
+1. Arguments normalization (norm() whitespace/case)
+2. Parallel calls (Counter multiset containment)
+3. Irrelevance (empty pred_names)
+4. Hard negatives (selection accuracy)
+5. Held-out tool generalization
+6. Argument type coercion
+7. Multi-turn context tracking
+8. Multi-hop chains
+9. Pure tool-calling (no chat dilution)
+10. Strict accuracy (selection + arguments)
+
+See also: [v7](https://huggingface.co/datasets/Nanthasit/sakthai-combined-v7)
+"""
+api.upload_file(
+    path_or_fileobj=readme.encode(),
+    path_in_repo="README.md",
+    repo_id=repo,
+    repo_type="dataset",
+)
+print("Uploaded README.md")
+print(f"\nDone: https://huggingface.co/datasets/{repo}")
+print(f"   Download: load_dataset('{repo}', split='train')")