```python
from safetensors.torch import load_file, save_file
import torch
import json

path = "/code/ComfyUI/models/controlnet/Shakker-Labs_FLUX.1-dev-ControlNet-Union-Pro.safetensors" # input file


# read safetensors metadata
def read_safetensors_metadata(path):
with open(path, "rb") as f:
header_size = int.from_bytes(f.read(8), "little")
header_json = f.read(header_size).decode("utf-8")
header = json.loads(header_json)
metadata = header.get("__metadata__", {})
return metadata


metadata = read_safetensors_metadata(path)
print(json.dumps(metadata, indent=4)) # show metadata

sd_pruned = dict() # initialize empty dict

state_dict = load_file(path) # load safetensors file
for key in state_dict: # for each key in the safetensors file
sd_pruned[key] = state_dict[key].to(torch.float8_e4m3fn) # convert to fp8

# save the pruned safetensors file
save_file(
sd_pruned,
"/code/ComfyUI/models/controlnet/Shakker-Labs_FLUX.1-dev-ControlNet-Union-Pro-fp8.safetensors",
metadata={"format": "pt", **metadata},
)

```