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Unlock the Power of BERT-based Models for Advanced Text Classification in Python

John Snow Labs

Text classification with transformers involves using a pretrained transformer model, such as BERT, RoBERTa, or DistilBERT, to classify input text into one or more predefined categories or labels. BERT (Bidirectional Encoder Representations from Transformers) is a language model that was introduced by Google in 2018.

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Text-to-Music Generative AI : Stability Audio, Google’s MusicLM and More

Unite.AI

Technical Insights The MusicLM leverages the principles of AudioLM , a framework introduced in 2022 for audio generation. An illustration of the pretraining process of MusicLM: SoundStream, w2v-BERT, and Mulan | Image source: here Moreover, MusicLM expands its capabilities by allowing melody conditioning.

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68 Summaries of Machine Learning and NLP Research

Marek Rei

EMNLP 2022. EMNLP 2022. NeurIPS 2022. EMNLP 2022. EMNLP 2022. They show performance improvements in some settings and speed improvements in all evaluated settings, showing particular usefulness in settings where the LLM needs to retrieve information about multiple entities (e.g. UC Berkeley, CMU. Google Research.

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Scaling Large Language Model (LLM) training with Amazon EC2 Trn1 UltraClusters

Flipboard

In October 2022, we launched Amazon EC2 Trn1 Instances , powered by AWS Trainium , which is the second generation machine learning accelerator designed by AWS. In this post, we use a Hugging Face BERT-Large model pre-training workload as a simple example to explain how to useTrn1 UltraClusters. run_dp_bert_large_hf_pretrain_bf16_s128.sh"

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Understanding the Power of Transformers: A Guide to Sentence Embeddings in Spark NLP

John Snow Labs

Specifically, it involves using pre-trained transformer models, such as BERT or RoBERTa, to encode text into dense vectors that capture the semantic meaning of the sentences. There is also a short section about generating sentence embeddings from Bert word embeddings, focusing specifically on the average-based transformation technique.

NLP 52
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An Overview of Instruction Tuning Data

Sebastian Ruder

With the arrival of pre-trained models such as BERT, fine-tuning pre-trained models for downstream tasks became the norm. 2022 ) : 193k instruction-output examples sourced from 61 existing English NLP tasks. 2022 ) : A crowd-sourced collection of instruction data based on existing NLP tasks and simple synthetic tasks.

NLP 52
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The State of Multilingual AI

Sebastian Ruder

Research models such as BERT and T5 have become much more accessible while the latest generation of language and multi-modal models are demonstrating increasingly powerful capabilities. This post is partially based on a keynote I gave at the Deep Learning Indaba 2022. The Deep Learning Indaba 2022 in Tunesia.