Upload merge_stage4_fixed.py with huggingface_hub

merge_stage4_fixed.py

@@ -0,0 +1,35 @@
+#!/usr/bin/env python3
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["torch", "transformers>=4.40.0", "peft>=0.10.0", "accelerate", "huggingface_hub>=0.21.0", "pillow", "qwen-vl-utils"]
+# ///
+import os, torch
+from huggingface_hub import login, HfApi
+from transformers import Qwen2VLForConditionalGeneration, AutoProcessor
+from peft import PeftModel
+from pathlib import Path
+
+login(token=os.environ.get("HF_TOKEN"))
+api = HfApi()
+
+print("Loading base model...")
+base = Qwen2VLForConditionalGeneration.from_pretrained(
+    "Qwen/Qwen2-VL-2B-Instruct", torch_dtype=torch.bfloat16, device_map="auto", trust_remote_code=True)
+processor = AutoProcessor.from_pretrained("Qwen/Qwen2-VL-2B-Instruct", trust_remote_code=True)
+
+print("Loading Stage 4 adapter...")
+model = PeftModel.from_pretrained(base, "mmrech/pitvqa-qwen2vl-unified-v2", adapter_name="stage4", subfolder="stage4")
+
+print("Merging...")
+merged = model.merge_and_unload()
+
+print("Saving...")
+out = Path("./pitvqa-merged")
+out.mkdir(exist_ok=True)
+merged.save_pretrained(out)
+processor.save_pretrained(out)
+
+print("Uploading...")
+api.create_repo("mmrech/pitvqa-qwen2vl-merged", exist_ok=True)
+api.upload_folder(folder_path=str(out), repo_id="mmrech/pitvqa-qwen2vl-merged", repo_type="model")
+print("Done! https://huggingface.co/mmrech/pitvqa-qwen2vl-merged")