app.py

from peft import PeftModel, PeftConfig
import torch
from datasets import load_dataset

torch.cuda.is_available()
print("executed successfully")

dataset_name = "timdettmers/openassistant-guanaco"
dataset = load_dataset(dataset_name, split="train")


import os

ld_library_path = os.environ.get("LD_LIBRARY_PATH")
print(ld_library_path)

# The directory to search in
search_directory = '/usr/'

# The filename pattern to look for (wildcard * is used)
filename_pattern = 'libcuda.so.*'

# Initialize a list to store the paths of matching files
matching_files = []

# Walk through the directory and its subdirectories
for root, dirs, files in os.walk(search_directory):
    for file in files:
        if file.startswith('libcuda.so.'):
            matching_files.append(os.path.join(root, file))

# Print the paths of matching files
for file in matching_files:
    print(file)