merge.py

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
from huggingface_hub import HfApi, login

BASE_MODEL = "microsoft/Phi-3-mini-4k-instruct"
ADAPTER = "BlueBoi32/testphimodel"
MERGED_PATH = "merged-model"
TARGET_REPO = "BlueBoi32/phi3-merged"  # CHANGE THIS

def merge_model():
    import os

    # Login using HF_TOKEN env var
    hf_token = os.environ.get("HF_TOKEN")
    if hf_token is None:
        raise ValueError("HF_TOKEN environment variable not found.")
    login(hf_token)

    print("Loading base model...")
    base = AutoModelForCausalLM.from_pretrained(
        BASE_MODEL,
        torch_dtype=torch.float16,
        device_map="cpu"
    )

    print("Loading LoRA adapter...")
    model = PeftModel.from_pretrained(base, ADAPTER)

    print("Merging LoRA → Base model...")
    model = model.merge_and_unload()

    print("Saving merged model locally...")
    model.save_pretrained(MERGED_PATH)
    tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL)
    tokenizer.save_pretrained(MERGED_PATH)

    print("Uploading merged model to HF Hub...")
    api = HfApi()
    api.upload_folder(
        folder_path=MERGED_PATH,
        repo_id=TARGET_REPO,
        token=hf_token
    )

    print("✅ Upload complete! Model is now at:", TARGET_REPO)