47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
|
import os
|
||
|
|
import json
|
||
|
|
from loguru import logger
|
||
|
|
import torch
|
||
|
|
|
||
|
|
from transformers import AutoTokenizer
|
||
|
|
from peft import AutoPeftModelForCausalLM, AutoPeftModelForSeq2SeqLM
|
||
|
|
|
||
|
|
def download_and_unload_peft(model_id, revision, trust_remote_code):
|
||
|
|
torch_dtype = torch.float16
|
||
|
|
|
||
|
|
logger.info("Peft model detected.")
|
||
|
|
logger.info("Loading the model it might take a while without feedback")
|
||
|
|
try:
|
||
|
|
model = AutoPeftModelForCausalLM.from_pretrained(
|
||
|
|
model_id,
|
||
|
|
revision=revision,
|
||
|
|
torch_dtype=torch_dtype,
|
||
|
|
trust_remote_code=trust_remote_code,
|
||
|
|
low_cpu_mem_usage=True,
|
||
|
|
)
|
||
|
|
except Exception:
|
||
|
|
model = AutoPeftModelForSeq2SeqLM.from_pretrained(
|
||
|
|
model_id,
|
||
|
|
revision=revision,
|
||
|
|
torch_dtype=torch_dtype,
|
||
|
|
trust_remote_code=trust_remote_code,
|
||
|
|
low_cpu_mem_usage=True,
|
||
|
|
)
|
||
|
|
logger.info(f"Loaded.")
|
||
|
|
logger.info(f"Merging the lora weights.")
|
||
|
|
|
||
|
|
base_model_id = model.peft_config["default"].base_model_name_or_path
|
||
|
|
|
||
|
|
model = model.merge_and_unload()
|
||
|
|
|
||
|
|
os.makedirs(model_id, exist_ok=True)
|
||
|
|
cache_dir = model_id
|
||
|
|
logger.info(f"Saving the newly created merged model to {cache_dir}")
|
||
|
|
tokenizer = AutoTokenizer.from_pretrained(base_model_id)
|
||
|
|
model.save_pretrained(cache_dir, safe_serialization=True)
|
||
|
|
model.config.save_pretrained(cache_dir)
|
||
|
|
tokenizer.save_pretrained(cache_dir)
|
||
|
|
|
||
|
|
|
||
|
|
|