Snorkel AI

MAY 25, 2023

This is why when fed the prompt “I went to see the New York,” the first token GPT-3 generates will almost always be a sports team or performance venue associated with the city. In April, DataBricks released Dolly 2.0. ” Overview of the scratchpad approach for predicting code execution.

Natural Language Processing 52

Natural Language Processing Python Machine Learning Machine Learning 52

O'Reilly Media

OCTOBER 19, 2021

In this article, we want to dig deeper into the fundamentals of machine learning as an engineering discipline and outline answers to key questions: Why does ML need special treatment in the first place? Why: Data Makes It Different. Why did something break? Can’t we just fold it into existing DevOps best practices?

ML 138

ML ML Data Scientist AWS 138

AWS Machine Learning Blog

NOVEMBER 14, 2023

For this, we will use the pre-trained 7 billion parameter Llama2 model and fine-tune it on the databricks-dolly-15k dataset. This is why we will use the QLoRA method to quantize the weights during finetuning to reduce this computation cost. Next, we fine-tune Llama2 on the databricks-dolly-15k dataset using the QLoRA method.

ML 89

ML ML AWS SQL 89

The MLOps Blog

OCTOBER 3, 2023

It was very interesting because by that point, I had approximately six years working with executive level leadership for companies like Autodesk, Teladoc, and other companies that are either very well known globally – or at least very, very well known domestically, within the US. How was my code?” There are three types of feature stores.

ML 52

ML ML Data Scientist Machine Learning 52

BAIR

FEBRUARY 17, 2024

In enterprises, our colleagues at Databricks found that 60% of LLM applications use some form of retrieval-augmented generation (RAG) , and 30% use multi-step chains. Why are developers building compound systems? Why Use Compound AI Systems? Why is that? Is this paradigm here to stay as models improve?

AI 145

AI AI DataOps Data Pipeline 145

Alation

JULY 18, 2022

That was the message — delivered a little more elegantly than that — at Databricks’ Data+AI Summit 2022. As a proud Databricks partner , Alation joined the data and analytics community for three days of keynotes, leadership remarks, and breakout sessions during the last week of June in San Francisco. and much more!

AI 52

AI AI Data Lakes Azure 52

AWS Machine Learning Blog

NOVEMBER 30, 2023

Databricks is getting up to 40% better price-performance with Trainium-based instances to train large-scale deep learning models. Trainium2’s performance, scale, and energy efficiency are some of the reasons why Anthropic has chosen to train its models on AWS, and will use Trainium2 for its future models. thousands of text documents).

AWS 125

AWS AI AI ML 125

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? These stages form a directed acyclic graph (DAG) to represent the order of execution. So let’s begin with a quick overview of all of these.

ML 52

ML ML Cross Validation Machine Learning 52

BAIR

FEBRUARY 18, 2024

In enterprises, our colleagues at Databricks found that 60% of LLM applications use some form of retrieval-augmented generation (RAG) , and 30% use multi-step chains. Why are developers building compound systems? Why Use Compound AI Systems? Why is that? Is this paradigm here to stay as models improve?

AI 40

AI AI DataOps Data Pipeline 40

The MLOps Blog

MARCH 21, 2023

Why are you building an ML platform? ” — Conor Murphy , Lead Data Scientist at Databricks, in “Survey of Production ML Tech Stacks” at the Data+AI Summit 2022 Your team should be motivated by MLOps to show everything that goes into making a machine learning model, from getting the data to deploying and monitoring the model.

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69