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download_base_weights.py

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+from transformers import ByT5Tokenizer, T5ForConditionalGeneration
+
+model_name = "google/byt5-base"
+print(f"Downloading and saving {model_name} locally...")
+
+# Download tokenizer and model
+tokenizer = ByT5Tokenizer.from_pretrained(model_name)
+model = T5ForConditionalGeneration.from_pretrained(model_name, use_safetensors=True)
+
+# Save to a NEW directory to keep it separate from your small model
+save_path = "./byt5_base_local_weights"
+tokenizer.save_pretrained(save_path)
+model.save_pretrained(save_path)
+
+print(f"Done! Weights are now in {save_path}")