# 模型构建model = models.Sequential()model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(32, 32, 3)))model.add(layers.MaxPooling2D((2, 2)))model.add(layers.Conv2D(64, (3, 3), activation='relu'))model.add(lay...
GitHub - facebookresearch/llama: Inference code for LLaMA modelsgithub.com/facebookresearch/llama...
In this course, AI-powered Python Applications: Building APIs for Generative AI Models, you'll harness the power of AI in production environments. First, you'll dive into creating REST APIs that effectively serve generative AI models, such as text generation, summarization, and data enrichment. ...
“autonomous driving” and “multimodal large language models”“autonomous driving challenges”and“lar...
model = tf.keras.models.Sequential([ tf.keras.layers.SimpleRNN(128, input_shape=(None, 10)), tf.keras.layers.Dense(10, activation='softmax') ]) Python的几个复杂AI算法框架: # 1. 深度强化学习 - DQN import gym import tensorflow as tf ...
人工智能(AI)是一个广泛而深入的领域,其中机器学习(Machine Learning)和深度学习(Deep Learning)是两大关键分支。神经网络(Neural Networks)作为深度学习的核心组件,在图像识别、自然语言处理、推荐系统等领域展现出了巨大的潜力。本教程将介绍如何使用Python和深度学习库(如TensorFlow或PyTorch)实现一个简单的前馈神经网络...
Python is one of the most popular languages used in AI/ML development. In this post, you will learn how to use NVIDIA Triton Inference Server to serve models within your Python code and environment using the new PyTriton interface. More specifically, you will learn how to prototype and tes...
In this step-by-step tutorial, you'll build a neural network from scratch as an introduction to the world of artificial intelligence (AI) in Python. You'll learn how to train your neural network and make accurate predictions based on a given dataset.
CoOp：Conditional Prompt Learning for Vision-Language Models (visual language task)CVNet：Correlation Verification for Image Retrieval (image retrieval)代码文件：CodeBERT：A Pre-Trained Model for Programming and Natural LanguagesCodeGen：A Conversational Paradigm for Program Synthesis Embedding 向量降维：Auto...
这些包不仅提供了高效的数据处理能力,还简化了复杂AI模型的训练与部署流程。下面,我们将探索几个在Python中广受欢迎的大模型包,并分享它们在实际应用中的价值。 1. TensorFlow 和PyTorch TensorFlow 和PyTorch 是目前最流行的深度学习框架,它们支持构建和训练大规模神经网络。尽管这两个框架本身并不直接提供“大模型包...