Google Research AI blog

FEBRUARY 28, 2023

Dataset Description Auto-Arborist A multiview urban tree classification dataset that consists of ~2.6M We also continued to release sustainability data via Data Commons and invite others to use it for their research. See some of the datasets and tools we released in 2022 listed below. Pfam-NUniProt2 A set of 6.8

Robotics 72

Robotics Deep Learning Auto-classification ML 72

Explosion

JANUARY 31, 2021

It’s much easier to configure and train your pipeline, and there are lots of new and improved integrations with the rest of the NLP ecosystem. And since modern NLP workflows often consist of multiple steps, there’s a new workflow system to help you keep your work organized. See NLP-progress for more results. Flair 2 89.7

NLP 52

NLP Python BERT Auto-classification 52

AWS Machine Learning Blog

MARCH 2, 2023

Sentiment analysis and other natural language programming (NLP) tasks often start out with pre-trained NLP models and implement fine-tuning of the hyperparameters to adjust the model to changes in the environment. script will create the VPC, subnets, auto scaling groups, the EKS cluster, its nodes, and any other necessary resources.

BERT 75

BERT Deep Learning Metadata Auto-complete 75

The MLOps Blog

JUNE 6, 2023

Bookmark for later Building MLOps Pipeline for NLP: Machine Translation Task [Tutorial] Building MLOps Pipeline for Time Series Prediction [Tutorial] Why do we need a model training pipeline? For example, Scikit-learn, a popular Python library, offers the Pipeline class to streamline preprocessing and model training.

ML 52

ML Machine Learning Auto-classification Auto-complete 52

AWS Machine Learning Blog

SEPTEMBER 6, 2023

Now you can also fine-tune 7 billion, 13 billion, and 70 billion parameters Llama 2 text generation models on SageMaker JumpStart using the Amazon SageMaker Studio UI with a few clicks or using the SageMaker Python SDK. What is Llama 2 Llama 2 is an auto-regressive language model that uses an optimized transformer architecture.

Auto-complete 97

Auto-complete Machine Learning ML Python 97

AWS Machine Learning Blog

MARCH 1, 2023

For information on incorporating autoscaling in your endpoint, see Going Production: Auto-scaling Hugging Face Transformers with Amazon SageMaker. For information on incorporating autoscaling in your endpoint, see Going Production: Auto-scaling Hugging Face Transformers with Amazon SageMaker.

Generative AI 80

Generative AI AI AI Auto-classification 80

Unite.AI

MARCH 28, 2024

Let's start by understanding why LLM inference is so challenging compared to traditional NLP models. The Inference Challenge with Large Language Models Before the advent of LLMs, natural language processing relied on smaller models focused on specific tasks like text classification, named entity recognition, and sentiment analysis.

Large Language Models 130

Large Language Models LLM Natural Language Processing Prompt Engineer 130

AWS Machine Learning Blog

NOVEMBER 1, 2023

The system is further refined with DistilBERT , optimizing our dialogue-guided multi-class classification process. Additionally, you benefit from advanced features like auto scaling of inference endpoints, enhanced security, and built-in model monitoring. TGI is implemented in Python and uses the PyTorch framework.

Auto-classification 92

Auto-classification LLM Auto-complete Generative AI 92

AWS Machine Learning Blog

JANUARY 17, 2024

Llama 2 is an auto-regressive generative text language model that uses an optimized transformer architecture. As a publicly available model, Llama 2 is designed for many NLP tasks such as text classification, sentiment analysis, language translation, language modeling, text generation, and dialogue systems.

Auto-complete 102

Auto-complete Python Deep Learning Machine Learning 102

AWS Machine Learning Blog

JANUARY 9, 2023

For example, an image classification use case may use three different models to perform the task. The scatter-gather pattern allows you to combine results from inferences run on three different models and pick the most probable classification model. These endpoints are fully managed and support auto scaling.

ML 74

ML Auto-complete Auto-classification Deep Learning 74

AWS Machine Learning Blog

AUGUST 8, 2023

In cases where the MME receives many invocation requests, and additional instances (or an auto-scaling policy) are in place, SageMaker routes some requests to other instances in the inference cluster to accommodate for the high traffic. First, a preprocessing model is applied to the input text tokenization (implemented in Python).

BERT 78

BERT Deep Learning Auto-classification ML 78