Developers face unique challenges when retrieving code snippets, such as understanding syntax, control flow, and variable dependencies. Enter SFR-Embedding-Code, a groundbreaking family of code embedding models that aims to address these challenges and revolutionize how we retrieve and generate code.
Now generally available, Agentforce for Developers represents a significant step in Salesforce's mission to drive innovation and deliver intelligent development tools. Let’s explore how Agentforce, powered by Salesforce AI Research’s large language models, is transforming the way you code.
The SFR-Embedding-Mistral marks a significant advancement in text-embedding models, building upon the solid foundations of E5-mistral-7b-instruct and Mistral-7B-v0.1.
TL;DR: We introduce INDICT, a novel framework that empowers Large Language Models (LLMs) with Internal Dialogues of Critiques for both safety and helpfulness guidance. The internal dialogue is a dual cooperative system between…
Equal contribution between Erik Nijkamp and Hiroaki Hayashi. PaperCodeTweet Abstract The family of Salesforce CodeGen models is growing with CodeGen2.5 – a small, but mighty model! While there has been a recent trend…
TLDR We trained a series of 7B LLMs named XGen-7B with standard dense attention on up to 8K sequence length for up to 1.5T tokens. We also fine tune the models on public-domain…
Speech recognition has been successfully depolyed on various smart devices, and is changing the way we interact with them. Traditional phonetic-based recognition approaches require training of separate components such as pronouciation, acoustic and language model.
