Computer Science, Computer Vision and Pattern Recognition
Author: LLama 2 7B Chat
Page 159/179
LLaMA-2, the next generation of LLaMA. Meta trained and released LLaMA-2 in three model sizes: 7, 13, and 70 billion parameters. The model architecture remains largely unchanged from that of LLaMA-1 models, but 40% more data was used to train the foundational models. The accompanying preprint also mentions a model with 34B parameters that might be released in the future upon satisfying safety targets.
Computer Science, Machine Learning
Predicting Hourly Building Electricity Consumption Using Historical and Forecast Weather Data
Computer Science, Computer Vision and Pattern Recognition
Enhancing Image Synthesis with CLIP-Based Loss Functions
Computer Science, Computer Vision and Pattern Recognition
Semi-Supervised Learning Techniques for Improved Image Classification
Exponential Stability of Damped Wave Equations: A Review
Computer Science, Cryptography and Security
Preparing a Diverse Dataset for Text-Based Information Security Evaluation
Rigorous Solution of the Gardner Problem in Random Processes
Instrumentation and Methods for Astrophysics, Physics
Offline Reinforcement Learning for Autonomous Scheduling of Astronomical Observation Campaigns
Electrical Engineering and Systems Science, Systems and Control
Data-Driven Kalman Filtering: A Promising Approach to Enhance Performance
Generic and Lifted Probabilistic Comparisons: Max Replaces Minmax
Computer Science, Machine Learning
Improving Edge Collaborative Inference Systems with Mixed Criterion NN
Computer Science, Computer Vision and Pattern Recognition
Facial Attributes for BMI Estimation: A Comparative Study of Deep Learning Models
Electrical Engineering and Systems Science, Image and Video Processing
Efficient Image Compression with Parallel Context Model
Physics, Statistical Mechanics
Random Processes and Replica Symmetry Breaking: A Comprehensive Review
Computer Science, Computer Vision and Pattern Recognition
A Model-Driven First Principles Approach to Pose Estimation: A Comparative Study of Random Variables and Deep Neural Networks
Mathematics, Numerical Analysis
Inverse Scattering Methods for Imaging and Reconstruction
Computer Science, Computer Vision and Pattern Recognition
Unlocking 3D Vision with Unsupervised Keypoint Discovery
Computer Science, Logic in Computer Science
Automating Service Composition with Behavioral Synthesis
Computer Science, Computers and Society
Scaffolding Code Writing with Parsons Problems: Understanding Efficacy Levels
Computer Science, Social and Information Networks