Meta - About Facebook

Introducing Muse Spark: MSL’s First Model, Purpose-Built to Prioritize People

Muse Spark powers a smarter and faster Meta AI assistant, and will be rolling out to WhatsApp, Instagram, Facebook, Messenger ...
InfoQ

Meta Details GEM Ads Model Using LLM-Scale Training, Hybrid Parallelism, and Knowledge Transfer

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Soroosh Khodami discusses why we aren't ready ...
GitHub

[Bug]: Qwen3-30b offline mode do not support offline data parallelism

import gc import torch from vllm import LLM, SamplingParams from vllm.distributed.parallel_state import (destroy_distributed_environment, destroy_model_parallel) def clean_up(): destroy_model_parallel ...
IEEE

Research on Model Parallelism and Data Parallelism Optimization Methods in Large Language Model—Based Recommendation Systems

Abstract: With the rapid adoption of large language models (LLMs) in recommendation systems, the computational and communication bottlenecks caused by their massive parameter sizes and large data ...
Scientific Research Publishing

Witte, K. (1992). Putting the Fear Back into Fear Appeals: The Extended Parallel Process Model. Communication Monographs, 59, 329-349.

ABSTRACT: The current systematic review study reviewed articles on public relations campaigns published between 2019 and 2024. It aimed to explore these articles regarding development, theories, ...
GitHub

Bitsandbytes quantization for litgpt 2d parallel model (TP+FSDP) within LightningTrainer

I'm trying to run inference within the LightningTrainer using a litgpt model with 2d parallelization (TP+FSDP) while using a Bitsandbytes precision plugin to enable quantization, however I get into ...