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script to retrieve the JumpStart model artifacts and deploy the pre-trained model to your local machine: python train_model.py encode("utf-8") import requests r2=requests.post(url="[link] data=request_body, headers={"Content-Type":"application/x-text","Accept":"application/json;verbose"}) print(r2.text) Run the train_model.py
The trafilatura library provides a command-line interface (CLI) and Python SDK for translating HTML documents in this fashion. The following code snippet demonstrates the librarys usage by extracting and preprocessing the HTML data from the Fine-tune Meta Llama 3.1 models using torchtune on Amazon SageMaker blog post.
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