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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

This innovative tool is designed for quantizing convolutional neural networks (CNNs). It allows for the transformation of both weights/biases and activations from 32-bit floating-point (FP32) to 8-bit integer (INT8) format, or even other bit depths. Utilizing this tool can greatly enhance inference performance and efficiency, all while preserving accuracy levels. It is compatible with various common layer types found in neural networks, such as convolution, pooling, fully-connected layers, and batch normalization, among others. Remarkably, the quantization process does not require the network to be retrained or the use of labeled datasets; only a single batch of images is sufficient. Depending on the neural network's size, the quantization can be completed in a matter of seconds to several minutes, facilitating quick updates to the model. Furthermore, this tool is specifically optimized for collaboration with DeePhi DPU and can generate the INT8 format model files necessary for DNNC integration. By streamlining the quantization process, developers can ensure their models remain efficient and robust in various applications.

Description

Accelerate the building, training, and deployment of models at scale through a fully managed infrastructure that provides essential tools and streamlined workflows. Launch personalized AI and LLMs on any infrastructure in mere seconds, effortlessly scaling inference as required. Tackle your most intensive tasks with batch job scheduling, ensuring you only pay for what you use on a per-second basis. Reduce costs effectively by utilizing GPU resources, spot instances, and a built-in automatic failover mechanism. Simplify complex infrastructure configurations by deploying with just a single command using YAML. Adjust to demand by automatically increasing worker capacity during peak traffic periods and reducing it to zero when not in use. Release advanced models via persistent endpoints within a serverless architecture, maximizing resource efficiency. Keep a close eye on system performance and inference metrics in real-time, tracking aspects like worker numbers, GPU usage, latency, and throughput. Additionally, carry out A/B testing with ease by distributing traffic across various models for thorough evaluation, ensuring your deployments are continually optimized for performance.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS)
FLUX.1
Gemma
Gemma 2
Google Cloud Platform
Jupyter Notebook
Kubernetes
LangChain
Llama 3
Llama 3.1
Llama 3.2
Mixtral 8x22B
Mixtral 8x7B
MusicGen
Pinecone
Stable Diffusion
Visual Studio Code
Vultr
Whisper

Integrations

Amazon Web Services (AWS)
FLUX.1
Gemma
Gemma 2
Google Cloud Platform
Jupyter Notebook
Kubernetes
LangChain
Llama 3
Llama 3.1
Llama 3.2
Mixtral 8x22B
Mixtral 8x7B
MusicGen
Pinecone
Stable Diffusion
Visual Studio Code
Vultr
Whisper

Pricing Details

$0.90 per hour
Free Trial
Free Version

Pricing Details

$100 + compute/month
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

DeePhi Quantization Tool

Website

aws.amazon.com/marketplace/pp/prodview-bwtx6kzwg3gva

Vendor Details

Company Name

VESSL AI

Founded

2020

Country

United States

Website

vessl.ai/

Product Features

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Alternatives

Alternatives