Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
An advanced End-to-End MLLM is designed to accept various forms of references and effectively ground responses. The Ferret Model utilizes a combination of Hybrid Region Representation and a Spatial-aware Visual Sampler, which allows for detailed and flexible referring and grounding capabilities within the MLLM framework. The GRIT Dataset, comprising approximately 1.1 million entries, serves as a large-scale and hierarchical dataset specifically crafted for robust instruction tuning in the ground-and-refer category. Additionally, the Ferret-Bench is a comprehensive multimodal evaluation benchmark that simultaneously assesses referring, grounding, semantics, knowledge, and reasoning, ensuring a well-rounded evaluation of the model's capabilities. This intricate setup aims to enhance the interaction between language and visual data, paving the way for more intuitive AI systems.
Description
Automating the reference checking process through online systems enables your team to save time, reduce the risk of human errors, and allows references to fill out surveys at their convenience. While finding reliable volunteers may prove challenging, verifying their backgrounds doesn’t have to be. There are candidates who might not align well with your organization’s values, and traditional background checks may overlook this issue. Enhance your organization's security with efficient reference checks that provide an additional safeguard. For a single fee per applicant, you can utilize our automated reference checking software to evaluate up to 50 references. This system facilitates the collection of fast and unbiased feedback from various references for all your candidates. You can distribute standardized reference questionnaires to as many individuals as you wish, making it simple to compile objective evaluations swiftly and efficiently. This streamlined process not only supports better hiring decisions but also fosters a more reliable vetting system.
API Access
Has API
No
API Access
Has API
No
Integrations
No details available.
Integrations
No details available.
Pricing Details
Free
Open source
Free Trial
No
Free Version
Yes
Pricing Details
$8.95 one-time payment
Free Trial
No
Free Version
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
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
No
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
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Apple
Founded
1976
Country
United States
Website
github.com/apple/ml-ferret
Vendor Details
Company Name
Interactive HR
Country
United States
Website
onlinereferencecheck.com
Product Features
Product Features
Reference Check
Audio References
No
Bulk Reference Request
Yes
Candidate Scoring
No
Completion Alerts
No
Email / Online
No
Mobile Access
No
Reminders
No
Reporting/Analytics
No
Survey Builder
Yes
Survey Library
Yes
Video References
No