Souvik Datta - MonsterAPI Blog

Souvik Datta

Txt2Img API Model Upgrade

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Txt2Img API Model Upgrade

We’ve transitioned from Stable Diffusion v1.5 to the Pix-Art-Sigma model. PixArt-Σ is a cutting-edge Diffusion Transformer model (DiT) that directly generates images in stunning 4K resolution. This upgrade brings a remarkable leap in quality, offering images with higher fidelity and better alignment with text prompts compared to its

Photomaker Optimization: Faster API and Lower Costs

Photomaker Optimization: Faster API and Lower Costs

We've significantly improved our Photomaker API, achieving a remarkable 45% increase in speed compared to the previous version and cutting serving costs by nearly 50%. These enhancements greatly enhance the efficiency and affordability of our services, providing users with faster responses and lower expenses. To achieve this, we've introduced a

What is LLaMa 3 and How It Differs from LLaMa 2

What is LLaMa 3 and How It Differs from LLaMa 2

What is LLaMa 3 and How It Differs from LLaMa 2 The world of large language models (LLMs) is constantly evolving, with new advancements pushing the boundaries of what's possible. Meta's recent release of LLaMa 3 has sparked significant interest, particularly compared to its predecessor, LLaMa 2. This blog post

SDXL Optimization: Faster API and Lower Costs

SDXL Optimization: Faster API and Lower Costs

We have successfully optimized our SDXL API, achieving a remarkable 45% increase in speed compared to our previous API and a nearly 50% reduction in serving costs. These improvements significantly elevate the efficiency and affordability of our services, benefiting users with super-faster responses and lower expenses. We've introduced two new

How to Choose the Right GPU for Finetuning LLMs?

How to Choose the Right GPU for Finetuning LLMs?

When fine-tuning Large Language Models (LLMs), selecting the right Graphics Processing Unit (GPU) is crucial. The ideal GPU can make or break the performance of your LLM fine-tuning tasks. Not only does it impact the performance you’ll get, but it will also decide how much you’ll be spending

Step-by-Step Guide to Finetuning SDXL

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Step-by-Step Guide to Finetuning SDXL

Today, we're super excited to announce the addition of fine-tuning support for SDXL 1.0, SD 2, and SD 2-1. Fine-tuning helps you to train SDXL on specific objects or styles, enabling the creation of a new model capable of generating images tailored to those objects or styles. In this

Gemma-2B LLM fine tuned on MonsterAPI outperforms LLaMA 13B on Maths reasoning

Gemma-2B LLM fine tuned on MonsterAPI outperforms LLaMA 13B on Maths reasoning

In this case study, we explore how a smaller, fine-tuned model like Gemma-2B can perform better than larger models while being far more efficient and fast. Using MonsterAPI's No-Code LLM fine-tuner - MonsterTuner, we finetuned Gemma-2B specifically for mathematical reasoning tasks, and we achieved a 68% performance boost over the

Introduction to LLMs - What Are LLMs, How Do LLMs Work?

Introduction to LLMs - What Are LLMs, How Do LLMs Work?

Overview of Large Language Models Large language models (LLMs) have revolutionized how AI models work. Large Language Models are similar to human intelligence. They are used for several things, including academia, tech, entertainment, and the research community. LLMs are trained on extensive data sets, they utilize intricate architectures like stack

Build a Retrieval-Augmented Generation ChatBot in 10 Minutes using MonsterAPI

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Build a Retrieval-Augmented Generation ChatBot in 10 Minutes using MonsterAPI

Retrieval Augmented Generation (RAG) is a technique that generates answers to pre-existing queries by combining pre-established rules or parameters (non-parametric memory) with external data from the internet (parametric memory). By responding in natural language conversations with contextually relevant responses, RAG bots are revolutionizing user interactions. We'll dive into the realm

How to fine-tune a Large Language Model (LLM) and deploy it on MonsterAPI

How to fine-tune a Large Language Model (LLM) and deploy it on MonsterAPI

Learn how to fine-tune an LLM without code using MonsterAPI’s no-code LLM finetuning and deploying it with just 1 click using Monster Deploy service. Using this service anyone can deploy an LLM with or without a LoRA Adapter with just a few clicks or commands. 💡Recently we did a

Outperforming SOTA LLMs for Less than the Cost of a Coffee with Monster Tuner

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Outperforming SOTA LLMs for Less than the Cost of a Coffee with Monster Tuner

Finetuning Mistral 7B LLM using Monster Tuner to outperform SOTA LLMs like Falcon and Zephyr.

Reshaping Education using AI powered Speech Processing for Underprivileged Youth

Unlocking Infinite Possibilities in Language Learning: Nudge & Monster API's Symphony of Innovation India is a diverse nation, home to numerous languages, dialects, and cultures. Within this diversity, English holds a vital position, acting as a tool for socioeconomic advancement and global communication. The/Nudge is an institute with a mission

Finetuning LLaMA 70B with No-Code: Results, Methods, and Implications

Finetuning LLaMA 70B with No-Code: Results, Methods, and Implications

In this blog post, we will demonstrate how you can effortlessly fine-tune the LLaMA 2 - 70B model at a fraction of the cost of $57.75 with just a few clicks, utilising the No-Code LLM-Finetuner from Monster API. Download the Fine-Tuned Model weights from Hugging Face Overview of LLaMa

MonsterAPI is now Integrated with Llama Index!

MonsterAPI is now Integrated with Llama Index!

In the ever-evolving realm of artificial intelligence, simplicity in accessing Language Models (LLMs) is essential. Developers and businesses continuously seek ways to harness the immense potential of these models to enhance their AI-driven applications. The combination of MonsterAPI with llama_index provides an invaluable solution to businesses for questioning meaningful

Text to Image SDXL API Guide

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Text to Image SDXL API Guide

Let's get started with our guide on using the Text-to-Image SDXL API from Monster API, powered by Stable Diffusion SDXL 1.0. This guide is designed to help developers smoothly integrate this technology into their applications. MonsterAPI gives developers access to powerful AI models, making it easier to create applications

How to Fine-Tune GPT-J on Alpaca GPT-4

How to Fine-Tune GPT-J on Alpaca GPT-4

We fine-tuned the GPT-J model with our MonsterAPI's MonsterTuner and the results were impressive. The GPT-J model comes with an impressive 6 billion parameters, making it an incredible option for fine-tuning for multiple use cases. We used the Alpaca GPT-4 dataset, which contains a collection of instructions paired with the

A guide on how to finetune llama 2 llm

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How to finetune Llama 2 LLM

LLaMA 2 is an impressive family of pre-trained and fine-tuned Large Language Models (LLMs) released by Meta AI ranging from 7B to 70B parameters (7B, 13B, 70B). As successors to the already impressive LLaMA 1, these newer versions are more refined, offering a host of enhancements that have everyone in

MonsterAPI no-code LLM finetuner

A guide on how to Finetune Large Language Models (LLMs) in 2024

Large Language Models (LLMs) have quickly become a sensation in the field of Natural Language Processing (NLP). The emergence of ChatGPT has further amplified the interest in LLMs as they possess the remarkable ability to generate text that closely resembles human language, offer prompt answers to queries, and actively engage

Introducing no-code LLM FineTuning with Monster API

Introducing no-code LLM FineTuning with Monster API

Introducing our no-code LLM fine-tuner. In just 3 simple steps, you'll be able to fine-tune open source LLMs, Whisper & SDXL models.

What is Falcon-7B Instruct? Is it a better alternative to GPT-3?

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What is Falcon-7B Instruct? Is it a better alternative to GPT-3?

What is Falcon-7B Instruct? Open source GPT-3 Alternative