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