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Average Ratings 0 Ratings
Description
ReinforceNow serves as a comprehensive platform dedicated to ongoing learning through AI agents, designed to assist teams in deploying, training, and iterating efficiently. Developers are empowered to create AI agents that can be continuously trained using production traffic, or they can opt for Claude Code to configure the setup automatically. The platform manages vital components such as reinforcement learning infrastructure, experiment orchestration, agent versioning, GPU training logic, and telemetry, allowing teams to concentrate on refining agent logic, data collection, and reward systems. With support for rapid LLM fine-tuning using LoRA, high-throughput training capabilities, and extensive compatibility with open-source models including Qwen, DeepSeek, and GPT-OSS, ReinforceNow enhances developers' efficiency. It offers sophisticated telemetry features that help evaluate, monitor, and iterate on AI agent LLM applications, including detailed traces, reward systems, experiment metrics, and training visibility. Teams can tackle extended tasks that require context sizes ranging from 32k to 1 million, create specialized agents for multi-turn interactions and long-duration tasks, and access an array of tools to streamline their reinforcement learning workflows, ultimately fostering innovation in AI development.
Description
Tinker is an innovative training API tailored for researchers and developers, providing comprehensive control over model fine-tuning while simplifying the complexities of infrastructure management. It offers essential primitives that empower users to create bespoke training loops, supervision techniques, and reinforcement learning workflows. Currently, it facilitates LoRA fine-tuning on open-weight models from both the LLama and Qwen families, accommodating a range of model sizes from smaller variants to extensive mixture-of-experts configurations. Users can write Python scripts to manage data, loss functions, and algorithmic processes, while Tinker autonomously takes care of scheduling, resource distribution, distributed training, and recovery from failures. The platform allows users to download model weights at various checkpoints without the burden of managing the computational environment. Delivered as a managed service, Tinker executes training jobs on Thinking Machines’ proprietary GPU infrastructure, alleviating users from the challenges of cluster orchestration and enabling them to focus on building and optimizing their models. This seamless integration of capabilities makes Tinker a vital tool for advancing machine learning research and development.
API Access
Has API
API Access
Has API
Integrations
Qwen
Amazon Web Services (AWS)
Claude Code
DeepSeek
Google Cloud Platform
Llama 3
Llama 3.1
Llama 3.2
Llama 3.3
Python
Integrations
Qwen
Amazon Web Services (AWS)
Claude Code
DeepSeek
Google Cloud Platform
Llama 3
Llama 3.1
Llama 3.2
Llama 3.3
Python
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
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
ReinforceNow
Country
United States
Website
www.reinforcenow.ai/
Vendor Details
Company Name
Thinking Machines Lab
Country
United States
Website
thinkingmachines.ai/tinker/