https://arxiv.org/abs/2212.04356 Embeddings Embeddings 是指文本的数字表示,可用于衡量两段文本之间的相关性。Embeddings 即嵌入,往往在搜索、聚类、推荐、异常检测和分类任务中拥有良好表现。 感兴趣的朋友可以在 OpenAI 的公告博文中了解关于最新...
Embeddings 是指文本的数字表示,可用于衡量两段文本之间的相关性。Embeddings 即嵌入,往往在搜索、聚类、推荐、异常检测和分类任务中拥有良好表现。 感兴趣的朋友可以在 OpenAI 的公告博文中了解关于最新嵌入模型的更多信息: https://openai.com/blog/new-embedding-models-and-api-updates Moderation Moderation 审核模型...
1.1 Text generation models OpenAI 的文本生成模型(通常被称为generative pre-trained transformers 模型...
OpenAITextEmbeddingGenerationService.GenerateEmbeddingsAsync Method Reference Feedback Definition Namespace: Microsoft.SemanticKernel.Connectors.OpenAI Assembly: Microsoft.SemanticKernel.Connectors.OpenAI.dll Package: Microsoft.SemanticKernel.Connectors.OpenAI v1.20.0 Important So...
publicSystem.Threading.Tasks.Task<System.Collections.Generic.IList<ReadOnlyMemory<float>>> GenerateEmbeddingsAsync (System.Collections.Generic.IList<string> data, Microsoft.SemanticKernel.Kernel? kernel =default, System.Threading.CancellationToken cancellationToken =default);...
Text generation.Embeddings are used to generate more coherent and contextually relevant text. Machine translation.Text embeddings can capture semantic meanings across languages, which can improve the quality of machine translation process. Getting Set Up ...
First-generation models (not recommended) 第一代模型(不推荐) Use cases 用例 Obtaining the embeddings 获取嵌入 Data visualization in 2D 二维数据可视化 Embedding as a text feature encoder for ML algorithms 嵌入作为ML算法的文本特征编码器 Regression using the embedding features 使用嵌入特征的回归 ...
Bring your imagination to life from text, image, or video. Learn more OpenAI o1 A new series of AI models designed to spend more time thinking before they respond. Learn more ChatGPT on your desktop ChatGPT on your desktop ChatGPT on your desktop Chat about email, screenshots, files, and...
/// /// Unit tests for <see cref="HuggingFaceTextEmbeddingGeneration"/> class. /// public class HuggingFaceEmbeddingGenerationTests : IDisposable { private const string Endpoint = "http://localhost:5000/embeddings";private const string Model = @"GanymedeNil/text2vec-large-chinese"; private...
embeddings 在 Sora 中的对应物称为 visual patches，tokenizer 对应的是 video compression network，应该是某种 convolutional VAEs (文章没有说明是不是 VQ-VAE)。具体做法是用 video compression network (visual encoder) 首先将输入视频的时间和空间维度同时进行压缩，编码成一个和视频大小成正比的 3D visual ...