Phi-4 Deploying Phi-4 on MonsterAPI Phi-4 is the latest model from Microsoft. The small-scale models are highly capable and offer incredible performance. Here's how to deploy Phi-4 on MonsterAPI.
Cloud hosting for LLMs Cloud vs. On-Premises: Choosing the Best Deployment Option for LLMs Cloud and on-premise LLM deployments come with their own set of advantages and challenges. Here's a deeper dive into cloud vs on-premise deployment.
CPU CPU vs. GPU: Key Differences & Uses Explained CPU & GPU may sound same, but they have some major differences. Here's a complete guide to breaking down the difference between CPU & GPU.
ORPO Fine-tuning Using ORPO to Improve LLM Fine-tuning with MonsterAPI ORPO is an innovative algorithm that simplifies the LLM fine-tuning process by directly integrating preference alignment into a single-step supervised fine-tuning. Here's how you can fine-tune LLMs with ORPO using MonsterAPI.
Upstream Difference Between Upstream & Downstream in Microservice The concept of upstream and downstream is often confusing for new developers. Understanding the difference between them can make a significant impact.
LLM fine-tuning Role of AI in Personalized Marketing Artificial intelligence is a game changer for marketers as it helps personalize, optimize, and automate many key marketing activities. Here's a breakdown of the role of AI in marketing in today's era.
neural networks How Neural Networks Work: A Beginner's Guide Neural networks are the foundation of technologies like natural language processing, computer vision, and generative AI. Here’s how they work.
improving inference times Achieving 62x Faster Inference than HuggingFace with MonsterDeploy In this case study, we compare the inference times of Hugging Face and MonsterDeploy. Here's how we achieved 50X faster inference than Hugging Face.
Artificial intelligence vs machine learning Artificial Intelligence vs Machine Learning vs Deep Learning - A Comprehensive Guide In this guide, we break down the difference between AI, ML, & DL. Dive deep into what these technologies mean, their application, and the challenges surrounding them.
LLM fine-tuning 5 Reasons Your Business Needs a Fine-Tuned AI Model Businesses can streamline their operations with fine-tuned LLMs. Not only that, they can do so much more. Read why businesses need fine-tuned LLMs in our comprehensive guide.
AI image tools 7 Best AI Image Generators for Creators and Marketers Which is the best AI image generation model? We've chosen the top 7 models that help marketers create high-definition images with simple text prompts.
AI statistics 2024 100+ Essential AI Statistics You Should Know for 2024 AI, the definitive technology of today & probably the future is changing life as we know it. The AI market is exploding and will continue to do so in the future. The growth of AI market can’t just be described in words. This is why we’ve compiled interesting
image to video Best 7 Image-to-Video AI Models in 2024 In this guide, we've compiled the best image-to-video models that can create stunning videos out of images. Here's our pick of the top image-to-video models.
searchGPT What is SearchGPT? Google’s Latest Opponent SearchGPT is the newest entry in the search engine space from OpenAI. In this guide, we're exploring what SearchGPT is and how it may change the search engine space forever.
LLMs for coding The Best Large Language Models (LLMs) for Coding: A Comprehensive Guide In this guide, we're covering all the best Large Language models you can use for code generation, their unique features, and how they boost productivity.
code development with AI How to Improve Code Suggestions With AI-Powered Development Tools In this guide, we’ll talk about the intricacies of improving code suggestions from AI tools, addressing both current inadequacies and potential pathways for enhancement.
llm evaluation performance How to Evaluate LLM Performance Using MonsterAPI Evaluating your LLM performance is essential to ensure you get quality output. Here's how to evaluate your LLM's performance with MonsterAPI.
image classification models Best Image Classification Models in 2024 You can find pre-trained models that can accomplish any task you want. These models, trained on a large corpus of data can capture patterns and features. There are models made specifically for image classifications. Using pre-trained models, developers can save on time and cost. Instead of doing hours of manual
llama 3.1 finetuning Building a Sarcastic Chatbot: A Case Study in Fine-Tuning and Deployment with MonsterAPI We ran a fun experiment and fine-tuned the LLaMa 3.1 8B model to create a sarcastic chatbot. Here's a complete breakdown of how we did it, and the fun results we got.
SDXL fine-tuning How to Fine-tune SDXL for Avatar Generation on MonsterAPI Convert your images into classy avatars by fine-tuning SDXL In just 3 steps, fine-tune SDXL and make your personal avatar generation agent.
Llama 3.2 Comprehensive Guide for Instruction Fine-tuning of LLaMa 3.2 using MonsterAPI In this blog, we'll teach you how to fine-tune a llama-3.2 model to generate code using the alpaca Python coding dataset. We'll use LORA, which preserves the pre-trained model knowledge while facilitating its seamless learning of new things.
Whisper Finetuning How to Finetune Whisper for Speech-to-Text Transcription Whisper Fine-tuning for speech-to-text transcription can be complicated if you don't know what to do. Use MonsterAPI's fine-tuning & deployment pipeline to streamline the process.
finetuning sdxl How to run a fine-tuned image generation SDXL model? Fine-tuning the SDXL model for your use case is complicated. Deploying the finetuned SDXL model is even more complex. So, we created this step by step guide on how to run SDXL model.
Data augmentation How to Build a Dataset for LLM Fine-tuning Building the right dataset for LLM fine-tuning makes all the performance for LLM fine-tuning. Here's how to build a dataset for LLM fine-tuning.
LoRA Finetuning 5 Reasons Why LoRA Adapters are the Future of Fine-Tuning LoRA (Low-Rank Adaption) is a game-changing solution for optimizing the fine-tuning of large language models. Here's how LoRA adapters are future of fine-tuning.
