Mistral 7B Blast Off - Making Hundreds of Templates in Seconds
TLDRIn this demo, Mark Heaps from Groq showcases the Mistral 7 Billion model's rapid email template generation capabilities. He demonstrates how quick iterations and variations can be achieved, emphasizing the model's efficiency and potential for use in CRM systems and digital assistants.
Takeaways
- ๐ Groq showcases the Mistral 7 Billion model, which is smaller and faster than the Llama 2 70 billion model.
- ๐ The demo focuses on the speed and performance of the Mistral 7 Billion model when used for generating email templates.
- โ๏ธ The model quickly generates an email template for a new electric vehicle launch in 2024, emphasizing a friendly and human tone.
- ๐ Iterative feedback is shown to refine the email, such as making it shorter and adding emphasis to visit the website.
- ๐ The model efficiently creates three variations of email templates based on the initial prompt, varying in tone and expression.
- ๐ฌ An auto-response email template is generated for customer inquiries, demonstrating adaptability to different communication needs.
- ๐ข The Mistral 7 Billion model achieves over 850 tokens per second per user, highlighting its high throughput.
- ๐ฃ๏ธ The video script suggests potential applications in speech-to-text and text-to-speech processes due to the model's low latency.
- ๐ป Groq claims to have over 800 models compiled in their system, offering a wide range of solutions for different needs.
- ๐ Groq does not make the Mistral 7 Billion model available to the public, but assures better performance for any model on their platform.
- ๐ง Contact information is provided for further inquiries, including an email address and website for trying out demos.
Q & A
Who is presenting the demo in the video?
-The demo is presented by Mark Heaps, Head of Brand at Groq.
What is the name of the smaller model discussed in the demo?
-The smaller model discussed in the demo is called Mistral 7 Billion.
What is the context of the use case shown in the demo?
-The context of the use case is creating email templates for customers, demonstrating the speed and performance of the Mistral 7 Billion model on Groq.
What is the initial prompt given to the Mistral 7 Billion model?
-The initial prompt is to write an email template about a new electric vehicle coming out in 2024, focusing on a friendly and human tone, and including a link to the website.
How does the presenter request the email to be shorter?
-The presenter requests the email to be shorter by saying 'make this email shorter' and keeping it friendly and natural.
What additional instructions are given to the model to improve the email?
-The presenter asks the model to add emphasis and incentive to visit the website.
How many email templates does the presenter request to be created based on the initial email?
-The presenter requests the creation of three email templates, varying in tone and expression.
What is the purpose of the auto response email requested in the demo?
-The auto response email is intended for when a customer contacts the company from the original email.
What is the rate of token generation per second per user mentioned in the demo?
-The rate of token generation per second per user is over 850 tokens.
How does the presenter describe the importance of low latency in speech to text and text back to speech processes?
-The presenter emphasizes that low latency and ultralow latency performance are crucial for a fluid experience when interacting with digital assistants.
How can viewers try the demo themselves?
-Viewers can try the demo by visiting Groq's website or reaching out via email at [email protected].
Outlines
๐ Groq's High-Speed LLM Demo
Mark Heaps, Head of Brand at Groq, introduces a demo showcasing the capabilities of Mistral 7 Billion, a smaller language model compared to Llama 2 70 billion. The demo emphasizes Groq's exceptional speed and performance, enabling quick iteration through prompts. The context provided is creating email templates for a new electric vehicle launch in 2024, with instructions to make the email sound friendly and include a website link. The model quickly generates a long email, which is then iteratively refined to be shorter, friendlier, and more enticing, demonstrating Groq's ability to handle natural language processing and generate variations of content.
Mindmap
Keywords
๐กGroq
๐กMark Heaps
๐กMistral 7 Billion
๐กLLM
๐กEmail Templates
๐กPrompts
๐กIteration
๐กTokens
๐กCRM
๐กAuto Response Email
๐กNatural Language Processing
Highlights
Mark Heaps, Head of Brand at Groq, introduces a demo using Mistral 7 Billion, a smaller language model.
The demo showcases the exceptional speed and performance of Groq hardware when running Mistral 7 Billion.
The use case involves creating email templates for customers with a prompt about a new electric vehicle.
The system quickly generates an email template, demonstrating the speed of token generation.
The initial email is too long, and the user requests a shorter version while maintaining a friendly tone.
The system iterates and provides a revised email template with a more concise and friendly tone.
The user asks for additional emphasis and incentive to visit the website, which the system successfully incorporates.
The system generates three variations of the email template with different tones and expressions.
The user is satisfied with the variations and plans to use them in a CRM system.
A request is made for an auto-response email template based on the original email.
The system provides a template for an auto-response email, showcasing its iterative capabilities.
The demo highlights the ability to get variations and options that can be loaded into a system.
The system's speed is emphasized, with over 850 tokens per second per user of generated tokens.
The importance of low latency and performance for a fluid experience with digital assistants is discussed.
The demo concludes with an invitation to try the demo on Groq's website and contact them for questions.
Groq claims to have over 800 models compiled in their system, offering a solution for various needs.
Mark Heaps assures that if Groq does not have a specific model, it will still run better on their hardware.