Upload convert_gguf.py with huggingface_hub

convert_gguf.py

@@ -4,22 +4,26 @@
 """Convert LoRA adapter to GGUF using Unsloth's built-in conversion."""
 
 import os
+import subprocess
+
+# Pre-install cmake to avoid interactive prompt
+print("Installing cmake...")
+subprocess.run(["apt-get", "update", "-qq"], check=True)
+subprocess.run(["apt-get", "install", "-y", "-qq", "cmake", "build-essential"], check=True)
+print("cmake installed!")
+
 from huggingface_hub import HfApi, create_repo
 
 # Config
-BASE_MODEL = "unsloth/functiongemma-270m-it"
 ADAPTER_MODEL = "victor/functiongemma-agent-finetuned"
 OUTPUT_REPO = "victor/functiongemma-agent-gguf"
 
 print("=" * 60)
 print("GGUF Conversion with Unsloth")
-print("=" * 60)
-print(f"Base: {BASE_MODEL}")
 print(f"Adapter: {ADAPTER_MODEL}")
 print(f"Output: {OUTPUT_REPO}")
 print("=" * 60)
 
-# Load model with adapter
 from unsloth import FastLanguageModel
 
 print("Loading model with LoRA adapter...")
@@ -38,7 +42,7 @@ try:
 except Exception as e:
     print(f"Repo creation: {e}")
 
-# Save as GGUF using Unsloth
+# Save as GGUF
 print("Converting to GGUF (q4_k_m)...")
 model.save_pretrained_gguf(
     "model",
@@ -56,5 +60,5 @@ api.upload_folder(
 
 print("=" * 60)
 print("DONE!")
-print(f"Model available at: https://huggingface.co/{OUTPUT_REPO}")
+print(f"Model: https://huggingface.co/{OUTPUT_REPO}")
 print("=" * 60)