Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
We offer fast and precise AI models optimized for deployment in production environments. Our inference API is designed for high availability, utilizing cutting-edge NVIDIA GPUs to ensure optimal performance. We have curated a selection of top open-source natural language processing (NLP) models from the community, making them readily available for your use. You have the flexibility to fine-tune your own models, including GPT-J, or upload your proprietary models for seamless deployment in production. From your user-friendly dashboard, you can easily upload or train/fine-tune AI models, allowing you to integrate them into production immediately without the hassle of managing deployment factors such as memory usage, availability, or scalability. Moreover, you can upload an unlimited number of models and deploy them as needed, ensuring that you can continuously innovate and adapt to your evolving requirements. This provides a robust framework for leveraging AI technologies in your projects.
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
Integrations
Python
Yes
Amazon Web Services (AWS)
Yes
Go
Yes
Google Cloud Platform
Yes
Inkling
No
Inkling-Small
No
Llama 3
No
Llama 3.1
No
Llama 3.2
No
Llama 3.3
No
Integrations
Python
Yes
Amazon Web Services (AWS)
No
Go
No
Google Cloud Platform
No
Inkling
Yes
Inkling-Small
Yes
Llama 3
Yes
Llama 3.1
Yes
Llama 3.2
Yes
Llama 3.3
Yes
Pricing Details
$29 per month
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
Yes
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
NLP Cloud
Founded
2021
Country
France
Website
nlpcloud.com
Vendor Details
Company Name
Thinking Machines Lab
Country
United States
Website
thinkingmachines.ai/tinker/
Product Features
Natural Language Generation
Business Intelligence
No
CRM Data Analysis and Reports
No
Chatbot
No
Email Marketing
No
Financial Reporting
No
Multiple Language Support
No
SEO
No
Web Content
No
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No