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@NanshaNansha To load a model locally using the PeftModel class from a pretrained model, you need to ensure that the base_model and other required files are available locally.
Try out these steps and let me know, if it works
Install the dependencies:- pip install transformers peft
Prepare Local Paths: Set the local paths where your pretrained model and cache directory are located.
example snippet:-
from peft import PeftModel
# Define the local path to the base model and the cache directory
base_model_path = 'path/to/your/base_model'
model_id = 'path/to/your/local_model_directory'
cache_dir = 'path/to/your/cache_directory'
# Load the model from the local path
model = PeftModel.from_pretrained(base_model_path, model_id=model_id, cache_dir=cache_dir)
# Example: Use the model for inference
# Make sure you have the tokenizer and other necessary components
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(base_model_path)
input_text = "Your input text here"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model(**inputs)
print(outputs)
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