FreeQAs
 Request Exam  Contact
  • Home
  • View All Exams
  • New QA's
  • Upload
PRACTICE EXAMS:
  • Oracle
  • Fortinet
  • Juniper
  • Microsoft
  • Cisco
  • Citrix
  • CompTIA
  • VMware
  • SAP
  • EMC
  • PMI
  • HP
  • Salesforce
  • Other
  • Oracle
    Oracle
  • Fortinet
    Fortinet
  • Juniper
    Juniper
  • Microsoft
    Microsoft
  • Cisco
    Cisco
  • Citrix
    Citrix
  • CompTIA
    CompTIA
  • VMware
    VMware
  • SAP
    SAP
  • EMC
    EMC
  • PMI
    PMI
  • HP
    HP
  • Salesforce
    Salesforce
  1. Home
  2. Oracle Certification
  3. 1z0-1127-24 Exam
  4. Oracle.1z0-1127-24.v2025-08-01.q35 Dumps
  • «
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • »
Download Now

Question 1

Which Oracle Accelerated Data Science (ADS) class can be used to deploy a Large Language Model (LLM) application to OCI Data Science model deployment?

Correct Answer: D
The Oracle Accelerated Data Science (ADS) class that can be used to deploy a Large Language Model (LLM) application to OCI Data Science model deployment is GenerativeAI. This class provides the necessary tools and functions to work with generative AI models, including deployment, fine-tuning, and inference capabilities. It integrates with OCI Data Science to streamline the process of deploying and managing LLM applications.
Reference
Oracle ADS documentation
Guides on deploying AI models using Oracle Data Science services
insert code

Question 2

Which component of Retrieval-Augmented Generation (RAG) evaluates and prioritizes the information retrieved by the retrieval system?

Correct Answer: A
insert code

Question 3

How does the utilization of T-Few transformer layers contribute to the efficiency of the fine-tuning process?

Correct Answer: A
insert code

Question 4

Which is a key advantage of usingT-Few over Vanilla fine-tuning in the OCI Generative AI service?

Correct Answer: D
The key advantage of using T-Few over Vanilla fine-tuning in the OCI Generative AI service is faster training time and lower cost. T-Few fine-tuning is designed to be more efficient by updating only a fraction of the model's parameters, which significantly reduces the computational resources and time required for fine-tuning. This efficiency translates to lower costs, making it a more economical choice for model fine-tuning.
Reference
Technical documentation on T-Few fine-tuning
Research articles comparing fine-tuning methods in machine learning
insert code

Question 5

You create a fine-tuning dedicated AI cluster to customize a foundational model with your custom training dat a. How many unit hours arc required for fine-tuning if the cluster is active for 10 hours?

Correct Answer: A
When you create a fine-tuning dedicated AI cluster and it is active for 10 hours, the number of unit hours required for fine-tuning is equal to the duration for which the cluster is active. Therefore, if the cluster is active for 10 hours, it requires 10 unit hours. This calculation assumes that the unit hour measurement directly corresponds to the active time of the cluster.
Reference
OCI documentation on unit hours and fine-tuning processes
Usage guidelines for dedicated AI clusters in OCI
insert code
  • «
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • »
[×]

Download PDF File

Enter your email address to download Oracle.1z0-1127-24.v2025-08-01.q35 Dumps

Email:

FreeQAs

Our website provides the Largest and the most Latest vendors Certification Exam materials around the world.

Using dumps we provide to Pass the Exam, we has the Valid Dumps with passing guranteed just which you need.

  • DMCA
  • About
  • Contact Us
  • Privacy Policy
  • Terms & Conditions
©2025 FreeQAs

www.freeqas.com materials do not contain actual questions and answers from Cisco's certification exams.