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#!/usr/bin/env python | |
import os | |
import sys | |
import logging | |
import torch | |
import diffusers | |
import safetensors | |
import safetensors.torch as sf | |
log = logging.getLogger("sd") | |
logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(levelname)s | %(message)s') | |
def convert(model_id, output_name): | |
if os.path.exists(output_name): | |
log.error(f'Output already exists: {output_name}') | |
return | |
pipe = diffusers.DiffusionPipeline.from_pretrained(model_id) | |
metadata = { 'model_id': model_id } | |
model = {} | |
model['state_dict'] = vars(pipe)['_internal_dict'] | |
for k in model['state_dict'].keys(): | |
# print(k, getattr(pipe, k)) | |
model[k] = getattr(pipe, k) | |
sf.save_model(model, output_name, metadata=metadata) | |
# log.info(f'Saved model: {output_name}') | |
if __name__ == "__main__": | |
sys.argv.pop(0) | |
if len(sys.argv) < 2: | |
log.info('Usage: hf-convert.py <model_id> <output_name>') | |
sys.exit(1) | |
log.debug(f'Packages: torch={torch.__version__} diffusers={diffusers.__version__} safetensors={safetensors.__version__}') | |
convert(sys.argv[0], sys.argv[1]) | |