This Python script creates a password-protected ZIP file using the pyzipper library. It allows you to specify the files to include in the ZIP and set a password for encryption. The resulting ZIP file requires the provided password to access its contents, providing an additional layer of security.
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Project: Project: Building a Domain Expert Model #47
Awesome 👏 👏 🎉
Congratulations on passing the "Introducing Generative AI with AWS" project 🔥 🏆 🥇
Greetings Learner, I am thrilled to extend my heartfelt congratulations on completing the Introducing Generative AI with AWS project! Learning new things and completing the project is never easy but you have done it gracefully. This is all because of your hard work and continuous evaluation. You have done a great job with the FineTuning Task Using AWS. I love the notebook, it is outstanding.
Your project demonstrates your proficiency in using the AWS to FineTune Generative AI model. These skills are highly valuable in the field, and your accomplishment is certainly commendable. But, still don't relax, keep exploring and learning from other references. These projects are just the starting phase of learning new things and there are many more complex things out there. So, start exploring and keep it up. 💪 💪
Take a moment to reflect on your journey throughout this project. Think about the challenges you encountered, the knowledge you acquired, and the personal growth you underwent. Celebrate your achievements and let this project serve as a foundation for advancing your skills and pursuing your aspirations in AI.
You can share your project on LinkedIn and ask the audience for necessary feedback or open the project for anyone to collaborate. This way you will find many interesting connections and engagement with others. For any queries or doubts related to the project you can ask on the knowledge portal as well.
I wish you all the best for your upcoming projects. Looking forward to your success. Happy Learning !!!
"Please don't forget to rate my work as a project reviewer! Your detailed feedback is very helpful and appreciated - Thank You!"
Evaluate the Pre-trained Llama2 Text Generation Large Language Model for Domain Knowledge
Fine-tuning a Large Language Model
Fine-tune a Large Language Model with a Domain-Specific Dataset
Evaluate the Fine-tuned Llama2 Large Language Model
Deploy the Fine-tuned Llama2 Model on AWS Sagemaker
Evaluate the Fine-tuned Llama2 Text Generation Large Language Model on Text Generation Tasks and Domain KnowledgeAwesome 👏 👏 🎉
Congratulations on passing the "Introducing Generative AI with AWS" project 🔥 🏆 🥇
Greetings Learner, I am thrilled to extend my heartfelt congratulations on completing the Introducing Generative AI with AWS project! Learning new things and completing the project is never easy but you have done it gracefully. This is all because of your hard work and continuous evaluation. You have done a great job with the FineTuning Task Using AWS. I love the notebook, it is outstanding.
Your project demonstrates your proficiency in using the AWS to FineTune Generative AI model. These skills are highly valuable in the field, and your accomplishment is certainly commendable. But, still don't relax, keep exploring and learning from other references. These projects are just the starting phase of learning new things and there are many more complex things out there. So, start exploring and keep it up. 💪 💪
Take a moment to reflect on your journey throughout this project. Think about the challenges you encountered, the knowledge you acquired, and the personal growth you underwent. Celebrate your achievements and let this project serve as a foundation for advancing your skills and pursuing your aspirations in AI.
You can share your project on LinkedIn and ask the audience for necessary feedback or open the project for anyone to collaborate. This way you will find many interesting connections and engagement with others. For any queries or doubts related to the project you can ask on the knowledge portal as well.
I wish you all the best for your upcoming projects. Looking forward to your success. Happy Learning !!!
"Please don't forget to rate my work as a project reviewer! Your detailed feedback is very helpful and appreciated - Thank You!"
Awesome 👏 👏 🎉 Congratulations on passing the "Introducing Generative AI with AWS" project 🔥 🏆 🥇 Greetings Learner, I am thrilled to extend my heartfelt congratulations on completing the Introducing Generative AI with AWS project! Learning new things and completing the project is never easy but you have done it gracefully. This is all because of your hard work and continuous evaluation. You have done a great job with the FineTuning Task Using AWS. I love the notebook, it is outstanding.
Your project demonstrates your proficiency in using the AWS to FineTune Generative AI model. These skills are highly valuable in the field, and your accomplishment is certainly commendable. But, still don't relax, keep exploring and learning from other references. These projects are just the starting phase of learning new things and there are many more complex things out there. So, start exploring and keep it up. 💪 💪
Take a moment to reflect on your journey throughout this project. Think about the challenges you encountered, the knowledge you acquired, and the personal growth you underwent. Celebrate your achievements and let this project serve as a foundation for advancing your skills and pursuing your aspirations in AI.
You can share your project on LinkedIn and ask the audience for necessary feedback or open the project for anyone to collaborate. This way you will find many interesting connections and engagement with others. For any queries or doubts related to the project you can ask on the knowledge portal as well.
I wish you all the best for your upcoming projects. Looking forward to your success. Happy Learning !!!
"Please don't forget to rate my work as a project reviewer! Your detailed feedback is very helpful and appreciated - Thank You!"
Useful Resources: Quick Concepts: Fine-Tuning in Generative AI(opens in a new tab) FineTuning vs RAG in Generative AI Applications(opens in a new tab) The Power of Domain-specific Gen AI(opens in a new tab) The Ultimate Guide to Domain-Specific AI(opens in a new tab) Pre-trained Model Evaluation
Deploy the Llama2 Model on AWS Sagemaker
Evaluate the Pre-trained Llama2 Text Generation Large Language Model for Domain Knowledge
Fine-tuning a Large Language Model
Fine-tune a Large Language Model with a Domain-Specific Dataset
Evaluate the Fine-tuned Llama2 Large Language Model
Deploy the Fine-tuned Llama2 Model on AWS Sagemaker
Evaluate the Fine-tuned Llama2 Text Generation Large Language Model on Text Generation Tasks and Domain KnowledgeAwesome 👏 👏 🎉 Congratulations on passing the "Introducing Generative AI with AWS" project 🔥 🏆 🥇 Greetings Learner, I am thrilled to extend my heartfelt congratulations on completing the Introducing Generative AI with AWS project! Learning new things and completing the project is never easy but you have done it gracefully. This is all because of your hard work and continuous evaluation. You have done a great job with the FineTuning Task Using AWS. I love the notebook, it is outstanding.
Your project demonstrates your proficiency in using the AWS to FineTune Generative AI model. These skills are highly valuable in the field, and your accomplishment is certainly commendable. But, still don't relax, keep exploring and learning from other references. These projects are just the starting phase of learning new things and there are many more complex things out there. So, start exploring and keep it up. 💪 💪
Take a moment to reflect on your journey throughout this project. Think about the challenges you encountered, the knowledge you acquired, and the personal growth you underwent. Celebrate your achievements and let this project serve as a foundation for advancing your skills and pursuing your aspirations in AI.
You can share your project on LinkedIn and ask the audience for necessary feedback or open the project for anyone to collaborate. This way you will find many interesting connections and engagement with others. For any queries or doubts related to the project you can ask on the knowledge portal as well.
I wish you all the best for your upcoming projects. Looking forward to your success. Happy Learning !!!
"Please don't forget to rate my work as a project reviewer! Your detailed feedback is very helpful and appreciated - Thank You!"
Useful Resources: Quick Concepts: Fine-Tuning in Generative AI(opens in a new tab) FineTuning vs RAG in Generative AI Applications(opens in a new tab) The Power of Domain-specific Gen AI(opens in a new tab) The Ultimate Guide to Domain-Specific AI(opens in a new tab) Pre-trained Model Evaluation
Deploy the Llama2 Model on AWS Sagemaker
Evaluate the Pre-trained Llama2 Text Generation Large Language Model for Domain Knowledge
Fine-tuning a Large Language Model
Fine-tune a Large Language Model with a Domain-Specific Dataset
Evaluate the Fine-tuned Llama2 Large Language Model
Deploy the Fine-tuned Llama2 Model on AWS Sagemaker
Evaluate the Fine-tuned Llama2 Text Generation Large Language Model on Text Generation Tasks and Domain Knowledge
AWS SUBIMITTION.zip
Building-a-Domain-Expert-Model-AWS
Fine-tuning a Large Language Model