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Description
Engaging in an intuitive process allows you to explore narratives through relatable human stories, while effectively utilizing contextual understanding and the collective knowledge of your team to enhance our specialized machine learning models. Our Narrative Engine connects your input to an extensive database of content, filtering and assembling the pieces that resonate with the nuances of your search into cohesive Narratives that you can scrutinize and monitor. With a versatile workflow, you can customize your focus on specific content creators and narrative amplifiers that pique your interest. You have the option to choose and refine content from a diverse library, observe how creators naturally cluster, or begin with a set of familiar creators to discover others aligned with your interests using our Community Machine Learning models. Furthermore, you can effortlessly track and analyze your Pendulum intelligence, transitioning from overarching summaries to individual content pieces, enabling the swift identification of emerging trends and possible risk factors. Additionally, exporting charts and data for the creation of comprehensive intelligence reports is a straightforward process that enhances your analytical capabilities. This seamless integration of various functionalities ensures that you stay ahead in a rapidly evolving information landscape.
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
Llama 3
Llama 3.1
Llama 3.2
Llama 3.3
Python
Qwen
Qwen3
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
Pendulum
Country
United States
Website
www.pendulumfn.com/our-platform
Vendor Details
Company Name
Thinking Machines Lab
Country
United States
Website
thinkingmachines.ai/tinker/
Product Features
Audience Intelligence
AI / Machine Learning
Audience Segmentation
Competitive Intelligence
Content Tracking
Data Visualization
Data-Driven Insights
Filters / Search
Image Recognition
Sentiment Analysis
Social Listening
Social Media Analytics
Trend Tracking
Media Monitoring
Alerts / Notifications
Broadcast Media Monitoring
Content Translation
Dashboards / Reporting
Export Results
Online News Monitoring
Podcast Monitoring
Print Media Monitoring
Social Media Monitoring