Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Instruction-following models like GPT-3.5 (text-DaVinci-003), ChatGPT, Claude, and Bing Chat have seen significant advancements in their capabilities, leading to a rise in their usage among individuals in both personal and professional contexts. Despite their growing popularity and integration into daily tasks, these models are not without their shortcomings, as they can sometimes disseminate inaccurate information, reinforce harmful stereotypes, and use inappropriate language. To effectively tackle these critical issues, it is essential for researchers and scholars to become actively involved in exploring these models further. However, conducting research on instruction-following models within academic settings has posed challenges due to the unavailability of models with comparable functionality to proprietary options like OpenAI’s text-DaVinci-003. In response to this gap, we are presenting our insights on an instruction-following language model named Alpaca, which has been fine-tuned from Meta’s LLaMA 7B model, aiming to contribute to the discourse and development in this field. This initiative represents a step towards enhancing the understanding and capabilities of instruction-following models in a more accessible manner for researchers.
Description
Reka Flash 3 is a cutting-edge multimodal AI model with 21 billion parameters, crafted by Reka AI to perform exceptionally well in tasks such as general conversation, coding, following instructions, and executing functions. This model adeptly handles and analyzes a myriad of inputs, including text, images, video, and audio, providing a versatile and compact solution for a wide range of applications. Built from the ground up, Reka Flash 3 was trained on a rich array of datasets, encompassing both publicly available and synthetic information, and it underwent a meticulous instruction tuning process with high-quality selected data to fine-tune its capabilities. The final phase of its training involved employing reinforcement learning techniques, specifically using the REINFORCE Leave One-Out (RLOO) method, which combined both model-based and rule-based rewards to significantly improve its reasoning skills. With an impressive context length of 32,000 tokens, Reka Flash 3 competes effectively with proprietary models like OpenAI's o1-mini, making it an excellent choice for applications requiring low latency or on-device processing. The model operates at full precision with a memory requirement of 39GB (fp16), although it can be efficiently reduced to just 11GB through the use of 4-bit quantization, demonstrating its adaptability for various deployment scenarios. Overall, Reka Flash 3 represents a significant advancement in multimodal AI technology, capable of meeting diverse user needs across multiple platforms.
API Access
Has API
No
API Access
Has API
No
Integrations
BERT
Yes
ChatGPT
Yes
Dolly
Yes
GPT-4
Yes
Llama
Yes
Ludwig
Yes
Nexus
No
Space
No
Stable LM
Yes
Integrations
BERT
No
ChatGPT
No
Dolly
No
GPT-4
No
Llama
No
Ludwig
No
Nexus
Yes
Space
Yes
Stable LM
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
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
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
Yes
Vendor Details
Company Name
Stanford Center for Research on Foundation Models (CRFM)
Country
United States
Website
crfm.stanford.edu/2023/03/13/alpaca.html
Vendor Details
Company Name
Reka
Founded
2022
Country
United States
Website
www.reka.ai/news/introducing-reka-flash