hf_utils.py

import json

import torch

from transformers.utils import CONFIG_NAME
from transformers.utils.hub import cached_file


def load_config_hf(model_name):
    resolved_archive_file = cached_file(model_name, CONFIG_NAME, _raise_exceptions_for_missing_entries=True, force_download=False)
    return json.load(open(resolved_archive_file))

def load_state_dict_hf(model_name, device=None, dtype=None):
    mapped_device = "cpu" if dtype not in [torch.float32, None] else device
    WEIGHTS_NAME = "Zamba2_2p7b_direct_from_pytorch.pt"
    resolved_archive_file = cached_file(model_name, WEIGHTS_NAME, _raise_exceptions_for_missing_entries=True, force_download=False)
    return torch.load(resolved_archive_file, map_location=mapped_device)