llm finetuning - MonsterAPI Blog

llm finetuning

A collection of 6 posts

Instruction Pre-Training of Language models using Monster-API

instruction pretraining

Instruction Pre-Training of Language models using Monster-API

Pre-training is a crucial step in the development of large-scale language models, forming the bedrock upon which their language understanding and generation capabilities are built.

Building text summarization & code generation bots with MonsterAPI

Choosing the Right LLMs & Fine-Tuning for Text Summarization & Code Generation?

In this blog, we’ll be walking you through the process of choosing the right LLM for text summarization and code generation and how to fine-tune them on MonsterAPI.

How to Fine-tune a Large Language Model

finetune gemma Featured

How to Fine-tune a Large Language Model

A comprehensive guide with fundamental concepts on how to fine-tune a large language model in 2024.

Unsloth & SDPA Integrated in MonsterAPI for 2x LLM Finetuning Performance Boost

Unsloth integration

Unsloth & SDPA Integrated in MonsterAPI for 2x LLM Finetuning Performance Boost

Finetuning LLMs to fit your business use case is crucial for building powerful Generative AI applications. Whether you’re developing a ChatGPT alternative or Chatbot for customer support or an email copywriting AI model, finetuning plays a critical role in improving the performance and quality for your specific application needs.

MonsterAPI is Now Integrated With Portkey - Here’s Everything You Need to Know

MonsterAPI is Now Integrated With Portkey - Here’s Everything You Need to Know

MonsterAPI is now integrated in Portkey, making it easier for developers to route LLM text generation requests directly to our cost-effective, scalable LLM APIs while using Portkey SDK.

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