Everytime I run this LLM I get a memory error. Please help.

importimport os
os

from transformers import RagTokenizer, RagRetriever, RagTokenForGeneration

from transformers import pipeline

Replace with the path to your local folder containing the text files

folder_path = "C:\Users\asokw\Downloads\new"

Function to read and process text files

def read_text_files(folder_path):

all_files = os.listdir(folder_path)


text_files = [os.path.join(folder_path, f) for f in all_files if f.endswith('.txt')]


documents = []





for file_path in text_files:


    with open(file_path, 'r', encoding='utf-8') as file:


        content = file.read()


        documents.append(content)





return documents

Load and preprocess documents

documents = read_text_files(folder_path)

Initialize RAG tokenizer, retriever, and model

tokenizer = RagTokenizer.from_pretrained('facebook/rag-token-base')

retriever = RagRetriever.from_pretrained('facebook/rag-token-base', index_name='exact', passages=documents)

model = RagTokenForGeneration.from_pretrained('facebook/rag-token-base', retriever=retriever)

your_prompt = "What information can be found in these documents?"

inputs = tokenizer(your_prompt, return_tensors="pt")

retrieval_output = model.get_retrieval_vector(inputs)

generation_inputs = {

"input_ids": inputs.input_ids,


"attention_mask": inputs.attention_mask,


"retrieval_logits": retrieval_output,

}

generation_output = model.generate(**generation_inputs)

generated_text = tokenizer.decode(generation_output.sequences[0])

print(f"Retrieved documents:", retrieval_output)

print(f"Generated text:", generated_text)

from transformers import RagTokenizer, RagRetriever, RagTokenForGeneration

from transformers import pipeline