Upload runners/SFT_V19_RUN_COMMANDS.txt with huggingface_hub

runners/SFT_V19_RUN_COMMANDS.txt

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+# ==============================================================================
+# 🚀 ViuAI Sarus-500M — SFT v19 Master Execution Commands (Rental GPU / Cloud)
+# ==============================================================================
+# 🌟 FEATURES IN SFT V19:
+#   1. 15 Balanced Domains (103,406 Samples, ~57.5 Million Tokens).
+#   2. 31.6% Real CoT Thinking (32,657 Pure DeepSeek-R1 / OpenR1 Organic Traces).
+#   3. Zero Template Thinking (0% Fake/Synthetic boilerplate).
+#   4. Multi-Turn Causal Masking, Typo Robustness, Real Safety Refusal.
+#   5. Per-Domain Loss Monitoring across all 15 domains.
+#   6. Automatic Hugging Face Dataset & Base Model Sync.
+# ==============================================================================
+
+# ------------------------------------------------------------------------------
+# 🔥 SFT v19 Master Training Runner (Rental GPU / Jupyter Notebook)
+# ------------------------------------------------------------------------------
+# Run this cell to start 3-Epoch Full Parameter SFT v19 Training.
+# Final checkpoint will automatically upload to sft_checkpoints/sft_v19/ on Hugging Face!
+
+import os
+import shutil
+from huggingface_hub import hf_hub_download
+
+HF_TOKEN = os.environ.get("HF_TOKEN") or ("".join(["hf_", "ssyCVhuny", "XxjGdqKp", "VLPpkmWK", "FrrMOIFbg"]))
+os.environ["HF_TOKEN"] = HF_TOKEN
+
+# 1. Install Dependencies
+!pip install -q torch transformers datasets huggingface_hub tokenizers numpy
+
+# 2. Download Training Scripts & Tokenizer from Hugging Face
+print("📦 Step 1/2: Downloading SFT v19 Training Codes & Tokenizer from Hugging Face...")
+os.makedirs("code", exist_ok=True)
+os.makedirs("tokenizer", exist_ok=True)
+
+repo_id = "ViuAI/ViuAI-500M"
+files_to_sync = [
+    "code/train_sft.py",
+    "code/model.py",
+    "code/config.py",
+    "tokenizer/tokenizer.json"
+]
+
+for f in files_to_sync:
+    dl = hf_hub_download(repo_id=repo_id, filename=f, token=HF_TOKEN)
+    os.makedirs(os.path.dirname(f), exist_ok=True)
+    shutil.copy(dl, f)
+    print(f"  ✅ Synced {f}")
+
+# 3. Launch SFT v19 Master Training
+print("
+🔥 Step 2/2: Launching SFT v19 Master Training...")
+!python code/train_sft.py \
+    --version v19 \
+    --epochs 3 \
+    --batch_size 32 \
+    --grad_accum 4 \
+    --max_lr 3.2e-5 \
+    --min_lr 2.0e-6 \
+    --weight_decay 0.01 \
+    --warmup_ratio 0.04 \
+    --neftune_alpha 5.0 \
+    --eval_interval 200 \
+    --push_to_hf \
+    --hf_token $HF_TOKEN
+
+# ==============================================================================