Sold by: Intuz
Deployed on AWS
Free Trial
AWS Free Tier
This product has charges associated with it for pre-configuration by Intuz Inc. This AMI comes with Hugging Face Transformers, Jupyter Notebook, and popular NLP models like GPT, BERT, and T5-ready to use for machine learning and natural language processing tasks.
Overview
This is a repackaged open source software product wherein additional charges apply for the pre-configuration and packaging by Intuz Inc.
The Hugging Face Transformers AMI by Intuz Inc offers a ready-to-launch environment for NLP developers and researchers. Pre-installed with Transformers library, Jupyter Notebook, and popular models like GPT, BERT, and T5, this AMI enables users to immediately begin fine-tuning or experimenting with state-of-the-art language models.
Whether you're building chatbots, performing sentiment analysis, or summarizing text, this pre-configured AMI streamlines your workflow on AWS without the hassle of manual setup or dependency conflicts.
This AMI is ideal for users who want to quickly test, prototype, and deploy NLP models on a secure EC2 instance-saving time while accelerating model development.
Highlights
- Pre-configured with Hugging Face Transformers, including GPT, BERT, and T5 models
- Launch-ready Jupyter Notebook environment for immediate development
- Designed for rapid NLP experimentation and deployment on AWS EC2
Details
Sold by
Categories
Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 22.04
Deployed on AWS
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Free trial
Try this product free for 5 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
m5a.large Recommended | $0.09 |
t3.micro AWS Free Tier | $0.09 |
m5dn.large | $0.09 |
g4dn.16xlarge | $0.09 |
m6a.2xlarge | $0.09 |
g4dn.2xlarge | $0.09 |
m6a.16xlarge | $0.09 |
m6a.48xlarge | $0.09 |
g4dn.12xlarge | $0.09 |
m6a.24xlarge | $0.09 |
Vendor refund policy
Intuz will not refund money in any case.However, you can cancel your subscription any time.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Pre-installed Hugging Face Transformers library with support for GPT, BERT, T5, and other popular models
Jupyter Notebook environment pre-configured for interactive development and testing
Includes all necessary Python libraries for running transformer-based NLP tasks out of the box
Optimized for AWS EC2 instances with GPU support
Secure, browser-accessible interface with default password set to the EC2 instance ID
Additional details
Usage instructions
After launching the instance, please allow 5-10 minutes for the environment to fully initialize. To access the Jupyter Notebook interface, open a web browser and navigate to http://<public-ip>:8080. Log in using the EC2 instance ID as the password. No additional configuration is required-Jupyter Notebook will launch with Hugging Face Transformers and supporting libraries pre-installed and ready to use. For advanced access, you may SSH into the instance using your key pair.
Support
Vendor support
We provide best effort technical support for this product. We will do our best to respond to your questions within the next 24 hours in business days. For any technical support or query, you can drop an email here: cloudsupport@intuz.com or fill up this form:
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Similar products
Hugging Face Neuron Deep Learning AMI (Ubuntu 22.04)
By Hugging Face
Hugging Face Neuron Deep Learning AMI (DLAMI) makes it easy to use Amazon EC2 Inferentia & Trainium instances for training and inference of Hugging Face Transformers and Diffusers models, offering up to 50% cost-to-train savings over comparable GPU-based DLAMIs.
Hugging Face Expert Support
By Hugging Face
Consulting service with access to leading experts in ML to support your AWS projects
Bert Small2bert
By Amazon Web Services
This is a Text Summarization model built upon a Transformer model from Hugging Face
Customer reviews
No customer reviews yet
Be the first to write a review for this product.