In this blog, we will show the summary of various open-source LLMs that we have benchmarked. We benchmarked these models from a latency, cost, and requests per second perspective. This will help you evaluate if it can be a good choice based on the business requirements. Please note that we

We benchmark the performance of Mistral-7B in this article from latency, cost, and requests per second perspective. This will help us evaluate if it can be a good choice based on the business requirements. Please note that we don't cover the qualitative performance in this article - there

We benchmark the performance of Falcon-40B-Instruct in this article from latency, cost, and requests per second perspective. This will help us evaluate if it can be a good choice based on the business requirements. Please note that we don't cover the qualitative performance in this article - there

We benchmark the performance of LLama2-70B in this article from latency, cost, and requests per second perspective. This will help us evaluate if it can be a good choice based on the business requirements. Please note that we don't cover the qualitative performance in this article - there

Deploying open-source Large Language Models (LLMs) at scale while ensuring reliability, low latency, and cost-effectiveness can be a challenging endeavor. Drawing from our extensive experience in constructing LLM infrastructure and successfully deploying it for our clients, I have compiled a list of the primary challenges commonly encountered by individuals in

We benchmark the performance of LLama2-13B in this article from latency, cost, and requests per second perspective. This will help us evaluate if it can be a good choice based on the business requirements. Please note that we don't cover the qualitative performance in this article - there

In the domain of language models, the practice of fine-tuning is widely adopted to tailor an existing language model for specific tasks and datasets. There are a lot of good resources online that describe what is fine tuning and what are the different parameter efficient techniques for it. This blog

This blog captures Llama 2 7B benchmarks - where a model excels and the areas where it struggles. Make informed decisions about its practical deployment. In this blog, we have benchmarked the Llama-2-7B model from NousResearch on huggingface.

Large language models (LLMs) are becoming increasingly powerful, and they are being used for a variety of tasks, including chatbots, text generation, and question-answering. However, LLMs can be expensive and resource-intensive to train. In this blog post, we will show you how to fine-tune a smaller LLM (7B) to perform

Table of Contents 1. Introduction to LLMOps 2. Essential Components of LLMOps 3. Benefits and Advantages of LLMOps 4. LLMOps Platforms and Tools 5. Conclusion Introduction to LLMOps LLMOps and its role in managing large language models LLMOps, also known as Large Language Model Operations, encompass the specialized practices and

In this article, we discuss about deploying Falcon model on your own cloud. The Technology Innovation Institute in Abu Dhabi has developed Falcon, an innovative series of language models. These models, released under the Apache 2.0 license, represent a significant advancement in the field. Notably, Falcon-40B stands out as

If ChatGPT is the iPhone, then the AppStore is yet to be built- and that will be a suite of vertical applications built on top of it. Every industry, every business, and every individual is going to build these applications in small and big ways. Starting from building a healthcare