CUDA VS Amazon SageMaker

CUDA Reviews

Amazon SageMaker Reviews

CUDA mentions (36)

• A comprehensive guide to running Llama 2 locally

  For my fellow Windows shills, here's how you actually build it on windows: Before steps: 1. (For Nvidia GPU users) Install cuda toolkit https://developer.nvidia.com/cuda-downloads 2. Download the model somewhere: https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/resolve/main/llama-2-13b-chat.ggmlv3.q4_0.bin In Windows Terminal with Powershell:

      git clone https://github.com/ggerganov/llama.cpp.

  - Source: Hacker News / 9 months ago

• Nvidia with linux....... not a good combination

  I use Ubuntu and configuring nvidia drivers is very easy installing from here https://developer.nvidia.com/cuda-downloads. Source: 10 months ago

• Can't get CLBLAST working on oobabooga

  You have posted almost no information about your Hardware and what exactly you have done. Do you actually have NVIDIA? Have you actually installed CUDA? Also when exactly do you get the error, while installed the python package or later? Source: 10 months ago

• NEW NVIDIA 535.98 DRIVER!!- INCREASE SPEED, POWER, IMAGE SIZE AN WHO KNOW WHAT ELSE MORE!

  EDIT: LINK TO CUDA-toolkit: https://developer.nvidia.com/cuda-downloads. Source: 11 months ago

• WizardLM-30B-Uncensored

  It's worth noting that you'll need a recent release of llama.cpp to run GGML models with GPU acceleration here is the latest build for CUDA 12.1), and you'll need to install a recent CUDA version if you haven't already (here is the CUDA 12.1 toolkit installer -- mind, it's over 3 GB). Source: 12 months ago

Amazon SageMaker mentions (36)

• Observations on MLOps–A Fragmented Mosaic of Mismatched Expectations

  Damn straight. Oh, wait, some vendors have claimed to build an end-to-end solution. But, meh, that’s marketing talk. Take, for example, a well-known platform like Amazon Sagemaker, which describes itself as “a fully managed service that brings together a broad set of tools to enable high-performance, low-cost machine learning (ML) for any use case.” It’s a great platform. My startup has even partnered with them.... - Source: dev.to / 8 days ago

• Sentiment Analysis with PubNub Functions and HuggingFace

  At this point, probably everyone has heard about OpenAI, GPT-4, Claude or any of the popular Large Language Models (LLMs). However, using these LLMs in a production environment can be expensive or nondeterministic regarding its results. I guess that is the downside of being good at everything; you could be better at performing one specific task. This is where HuggingFace can utilized. HuggingFace provides... - Source: dev.to / 29 days ago

• Beginning the Journey into ML, AI and GenAI on AWS

  Generative Artificial Intelligence (GenAI) is a type of artificial intelligence that can generate text, images, or other media using generative models. AWS offers a range of services for building and scaling generative AI applications, including Amazon SageMaker, Amazon Rekognition, AWS DeepRacer, and Amazon Forecast. AWS has also invested in developing foundation models (FMs) for generative AI, which are... - Source: dev.to / 3 months ago

• Technical Architecture for LLMOps

  Amazon and Azure already have much of what you're talking about in AWS SageMaker and Azure MLOps. Source: 11 months ago

• Are AI fine-tuning tools worth learning and investing?

  And there have been several platforms that help fine-tune pretrained models, such as Google Cloud AutoML and Amazon Sagemaker. These tools are often fairly easy to use, but they come at a cost. They can be expensive, depending on the size of your dataset. Another option is Finetuner+, that also fine-tunes like AutoML and Sagemaker. The big advantage is that you don't need to transfer your data to other GPUs,... Source: about 1 year ago