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import sys
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- # TODO: Update ../requirements.txt
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+ # TODO: Update ` ../requirements.txt`.
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# from transformers import AutoTokenizer, AutoModelForSequenceClassification
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def download_models ():
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- # TODO: Set this to your model's Hugging Face identifier
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+ # TODO: Set this to your model's Hugging Face identifier.
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MODEL_IDENTIFIER = ""
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# TODO: Configure the model(s) needed for this module.
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- # Download the model(s) and tokenizer(s) for your module from the Hugging Face model hub
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+ # Download the model(s) and tokenizer(s) for your module from the Hugging Face model hub.
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# https://huggingface.co/docs/hub/en/models-downloading
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if not MODEL_IDENTIFIER :
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print (
@@ -22,7 +22,7 @@ def download_models():
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try :
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print (f"Downloading model `{ MODEL_IDENTIFIER } `..." )
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- # TODO: Initialize `model` and `tokenizer`
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+ # TODO: Initialize `model` and `tokenizer`.
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# tokenizer = AutoTokenizer.from_pretrained(MODEL_IDENTIFIER)
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# model = AutoModelForSequenceClassification.from_pretrained(MODEL_IDENTIFIER)
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tokenizer .save_pretrained ("./models" )
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import traceback
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import json
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- # TODO: Update ../requirements.txt
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+ # TODO: Update ` ../requirements.txt`.
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# import torch
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# from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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@@ -48,7 +48,7 @@ def main():
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output = {"input" : input , "status" : "error" }
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try :
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- # TODO: Initialize `model` and `tokenizer`
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+ # TODO: Initialize `model` and `tokenizer`.
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# model = AutoModelForSeq2SeqLM.from_pretrained(model_directory)
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# tokenizer = AutoTokenizer.from_pretrained(model_directory)
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