push_model.py

"""Push Borealis model to HuggingFace Hub."""

import os
import torch
from huggingface_hub import HfApi, create_repo, upload_folder
from safetensors.torch import save_model

# Config
HF_REPO = "Vikhrmodels/Borealis-5b-it"
CHECKPOINT_PATH = "/home/alex/Borealis/borealis_instruct_ckpts/checkpoint-2898/pytorch_model.bin"
OUTPUT_DIR = "/home/alex/Borealis/hf_upload"

class DictModule(torch.nn.Module):
    """Wrapper to use save_model with state_dict."""
    def __init__(self, state_dict):
        super().__init__()
        for k, v in state_dict.items():
            # Replace dots with underscores for valid attr names
            self.register_buffer(k.replace(".", "__DOT__"), v)

    def state_dict(self, *args, **kwargs):
        sd = super().state_dict(*args, **kwargs)
        return {k.replace("__DOT__", "."): v for k, v in sd.items()}

def main():
    print(f"Loading checkpoint from {CHECKPOINT_PATH}...")
    state_dict = torch.load(CHECKPOINT_PATH, map_location="cpu", weights_only=False)
    print(f"Loaded {len(state_dict)} keys")

    # Handle shared tensors by cloning
    print("Handling shared tensors...")
    new_state_dict = {}
    for k, v in state_dict.items():
        new_state_dict[k] = v.clone()

    # Convert to safetensors using save_model
    print("Converting to safetensors format...")
    safetensors_path = os.path.join(OUTPUT_DIR, "model.safetensors")

    from safetensors.torch import save_file
    save_file(new_state_dict, safetensors_path)
    print(f"Saved to {safetensors_path}")

    # Create repo
    print(f"\nCreating/accessing repo: {HF_REPO}")
    api = HfApi()
    try:
        create_repo(HF_REPO, repo_type="model", exist_ok=True)
    except Exception as e:
        print(f"Repo note: {e}")

    # Upload folder
    print(f"\nUploading to {HF_REPO}...")
    api.upload_folder(
        folder_path=OUTPUT_DIR,
        repo_id=HF_REPO,
        repo_type="model",
    )

    print(f"\nDone! Model available at: https://huggingface.co/{HF_REPO}")

if __name__ == "__main__":
    main()