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import torch |
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from typing import Tuple |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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tokenizer = None |
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model = None |
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def get_model_and_tokenizer() -> Tuple[AutoModelForCausalLM, AutoTokenizer]: |
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""" |
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Returns the preloaded model and tokenizer. If they haven't been loaded before, loads them. |
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Returns: |
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tuple: A tuple containing the preloaded model and tokenizer. |
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""" |
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global model, tokenizer |
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if model is None or tokenizer is None: |
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
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tokenizer = AutoTokenizer.from_pretrained("juancopi81/lmd_8bars_tokenizer") |
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model = AutoModelForCausalLM.from_pretrained( |
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"juancopi81/lmd-8bars-2048-epochs40_v4" |
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) |
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model = model.to(device) |
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return model, tokenizer |
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