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from sentence_transformers import CrossEncoder
import os
# Define the model name and the directory to save it to
MODEL_NAME = 'cross-encoder/nli-roberta-base'
MODEL_PATH = './sentiment_model'
def main():
"""
Downloads the specified model from Hugging Face and saves it locally.
"""
print(f"Downloading model: {MODEL_NAME}")
# Check if the directory exists
if not os.path.exists(MODEL_PATH):
os.makedirs(MODEL_PATH)
# This command downloads the model and saves it to the specified path
model = CrossEncoder(MODEL_NAME)
model.save(MODEL_PATH)
print(f"Model downloaded and saved to {MODEL_PATH}")
if __name__ == "__main__":
main() |