from transformers import ByT5Tokenizer, T5ForConditionalGeneration

model_name = "google/byt5-small"
print("Downloading and saving model locally...")

tokenizer = ByT5Tokenizer.from_pretrained(model_name)
# This forces the download of the safetensors version
model = T5ForConditionalGeneration.from_pretrained(model_name, use_safetensors=True)

# Save to a local directory in your project folder
tokenizer.save_pretrained("./byt5_local_weights")
model.save_pretrained("./byt5_local_weights")

print("Done! Weights are now in ./byt5_local_weights")