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features
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support

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Description

BHK Cloud is a cloud infrastructure service located in Frankfurt, designed specifically for AI and data-heavy tasks. The platform offers access to on-demand RTX 3090 GPUs with 24 GB of VRAM, starting at a competitive rate of $0.15 per GPU hour. Additionally, it features S3-compatible object storage available from $2.50 per terabyte per month without any egress fees, along with managed hosting for AI agents. Users can easily provision resources via a REST API or command-line interface, launch environments tailored for popular frameworks like PyTorch, TensorFlow, and CUDA, and integrate storage volumes while utilizing existing S3 tools such as AWS CLI and boto3 through a compatible interface. Operated out of Frankfurt, BHK Cloud is ideal for teams requiring data residency within Europe, offering transparent usage-based pricing with no minimum contract obligations. The platform also accommodates a variety of tasks including model inference, image creation, fine-tuning with LoRA or QLoRA, video processing, and managing backups and archives, thereby catering to extensive model or data workflows. This versatility makes BHK Cloud a comprehensive solution for organizations looking to leverage advanced cloud capabilities for their AI and data needs.

Description

TorchMetrics comprises over 90 implementations of metrics designed for PyTorch, along with a user-friendly API that allows for the creation of custom metrics. It provides a consistent interface that enhances reproducibility while minimizing redundant code. The library is suitable for distributed training and has undergone thorough testing to ensure reliability. It features automatic batch accumulation and seamless synchronization across multiple devices. You can integrate TorchMetrics into any PyTorch model or utilize it within PyTorch Lightning for added advantages, ensuring that your data aligns with the same device as your metrics at all times. Additionally, you can directly log Metric objects in Lightning, further reducing boilerplate code. Much like torch.nn, the majority of metrics are available in both class-based and functional formats. The functional versions consist of straightforward Python functions that accept torch.tensors as inputs and yield the corresponding metric as a torch.tensor output. Virtually all functional metrics come with an equivalent class-based metric, providing users with flexible options for implementation. This versatility allows developers to choose the approach that best fits their coding style and project requirements.

API Access

Has API

API Access

Has API

Screenshots View All

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Integrations

PyTorch
Kubernetes
Lightning AI
OpenClaw
TensorFlow

Integrations

PyTorch
Kubernetes
Lightning AI
OpenClaw
TensorFlow

Pricing Details

$0.15 per GPU hour
Free Trial
Free Version

Pricing Details

Free
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

BHK Cloud

Country

Germany

Website

ai.bhkcloud.com

Vendor Details

Company Name

TorchMetrics

Country

United States

Website

torchmetrics.readthedocs.io/en/stable/

Product Features

Product Features

Application Development

Access Controls/Permissions
Code Assistance
Code Refactoring
Collaboration Tools
Compatibility Testing
Data Modeling
Debugging
Deployment Management
Graphical User Interface
Mobile Development
No-Code
Reporting/Analytics
Software Development
Source Control
Testing Management
Version Control
Web App Development

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