Embedding

Code embeddings are a transformative solution to represent code snippets as dense vectors in a continuous space. These embeddings capture the semantic and functional relationships between code snippets, enabling powerful applications in AI-assisted programming....

Selecting the model that works best on your dataThe important thing observations from these results are:Best performances were obtained by open-source models. The BGE-M3 model, developed by the Beijing Academy of Artificial Intelligence, emerged...

An open source text embedding model has emerged that is alleged to have higher performance than OpenAI's 'text-embedding-ada-002', the perfect currently available. Through this, it's evaluated that the open source large language model...

We're launching a recent generation of embedding models, recent GPT-4 Turbo and moderation models, recent API usage management tools, and shortly, lower pricing on GPT-3.5 Turbo.

A series of articles on constructing an accurate Large Language Model for neural search from scratch. We’ll start with BERT and sentence-transformers, undergo semantic search benchmarks like BEIR, modern models like SGPT and E5,...

Essential guide to transfer learningOther Details for ConvNeXt models:Implementation:Instantiate the ConvNeXt-Tiny model using the below-mentioned code:tf.keras.applications.ConvNeXtTiny(model_name="convnext_tiny",include_top=True,include_preprocessing=True,weights="imagenet",input_tensor=None,input_shape=None,pooling=None,classes=1000,classifier_activation="softmax",)The above-mentioned code is for ConvNeXt-Tiny implementation, keras offers an identical API of the opposite EfficientNet architecture (ConvNeXt-Small, ConvNeXt-Base,...

VC Astasia Myers’ perspectives on machine learning, cloud infrastructure, developer tools, open source, and security. Join here.While AI has had an extended history, we're currently in a ML boom that began with the transition...

Unification of capabilities. We've got significantly simplified the interface of the /embeddings endpoint by merging the five separate models shown above (text-similarity, text-search-query, text-search-doc, code-search-text and code-search-code) right into a single recent model. This single representation performs higher than our previous...