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Description

Fine-tuning involves utilizing a dataset to develop a model compatible with AI applications. Achieving this can be challenging without programming skills, which is why we've integrated a straightforward solution into RIku that simplifies the entire process. By leveraging fine-tuning, you can tap into an enhanced level of AI capabilities, and we are thrilled to support you in this journey. Additionally, Public Share Links serve as unique landing pages that can be created for any prompts you design. These pages can be customized to reflect your brand identity, featuring your choice of colors, logo, and personalized welcome messages. You can share these links publicly, allowing others to access them and generate content if they possess the necessary password. This feature acts as a micro-scale, no-code writing assistant tailored for your audience! One notable challenge we've encountered in projects utilizing various large language models is the subtle variations in their output, which can sometimes lead to inconsistencies. By addressing these discrepancies, we aim to streamline the user experience and enhance the coherence of generated content.

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 Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Airtable Yes 
Google Sheets Yes 
Inkling No 
Inkling-Small No 
Llama 3 No 
Llama 3.1 No 
Llama 3.2 No 
Llama 3.3 No 
Make Yes 
Pabbly Connect Yes 
Python No 
Qwen No 
Qwen3 No 
Zapier Yes 

Integrations

Airtable No 
Google Sheets No 
Inkling Yes 
Inkling-Small Yes 
Llama 3 Yes 
Llama 3.1 Yes 
Llama 3.2 Yes 
Llama 3.3 Yes 
Make No 
Pabbly Connect No 
Python Yes 
Qwen Yes 
Qwen3 Yes 
Zapier No 

Pricing Details

$29 per month
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Riku

Website

riku.ai/

Vendor Details

Company Name

Thinking Machines Lab

Country

United States

Website

thinkingmachines.ai/tinker/

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