NVIDIA Generative AI LLMs - NCA-GENL Free Exam Questions

A. To optimize the model's inference speed for production deployment.

B. To identify and mitigate potential biases, safety risks, and harmful outputs.

C. To increase the model's parameter count for better performance.

D. To automate the collection of training data for fine-tuning.

A. Training deep learning models

B. Inspecting, cleansing, and transforming data

C. Performing GPU-accelerated machine learning tasks

D. Data visualization and analysis

A. Simplified API for classical machine learning algorithms like SVM.

B. Seamless integration with PyTorch and TensorRT for GPU-accelerated training and inference.

C. Built-in support for CPU-based data preprocessing pipelines.

D. Automatic conversion of models to ONNX format for cross-platform deployment.

A. BERT

B. Word2vec

C. WordNet

D. TensorRT

E. Kubernetes

A. Fine tuning a model

B. Zero-shot learning

C. One-shot learning

D. Few-shot learning

A. To determine the order in which words are generated.

B. To measure the importance of the words in the output sequence.

C. To assign weights to each word in the input sequence.

D. To capture the order of the words in the input sequence.

A. SVM model

B. Auto-encoder model

C. Encoder model

D. Siamese model

A. Any model validated by the artificial intelligence safety institute as the foundation for building transformer-based applications.

B. A model that sets the state-of-the-art results for any of the tasks that compose the General Language Understanding Evaluation (GLUE) benchmark.

C. Any model trained on vast quantities of data at scale whose goal is to serve as a starter that can be adapted to a variety of downstream tasks.

D. Any model based on the foundation paper "Attention is all you need," that uses recurrent neural networks and convolution layers.

A. A branch of artificial intelligence that focuses on improving the efficiency of existing models.

B. A branch of artificial intelligence that focuses on analyzing and interpreting existing data.

C. A branch of artificial intelligence that focuses on auto generation of models for classification.

D. A branch of artificial intelligence that focuses on creating models that can generate new and original data.

A. Images from a prompt description.

B. Outputs are only similar to the input data.

C. Grammatically incorrect or broken outputs.

D. Correct sounding results that are wrong.