LLM and Fine-tuning
A Practical Guide to Integrate Evaluation and Observability into LLM Apps
A comprehensive guide to Opik, an open-source LLM evaluation and observability framework.
LLM and Fine-tuning
A collection of 10 posts
LLM and Fine-tuning
A Beginner-friendly and Comprehensive Deep Dive on Vector Databases
Understanding every little detail on vector databases and their utility in LLMs, along with a hands-on demo.
LLM and Fine-tuning
LLM Fine-tuning
LLM and Fine-tuning
Implementing LLaMA 4 from Scratch
A from-scratch implementation of Llama 4 LLM, a mixture-of-experts model, using PyTorch code.
LLM and Fine-tuning
AugSBERT: Bi-encoders + Cross-encoders for Sentence Pair Similarity Scoring – Part 2
A deep dive into extensions of cross-encoders and bi-encoders for sentence pair similarity.
LLM and Fine-tuning
Bi-encoders and Cross-encoders for Sentence Pair Similarity Scoring (Part 1)
A deep dive into why BERT isn't effective for sentence similarity and advancements that shaped this task forever.
LLM and Fine-tuning
Augmenting LLMs: Fine-Tuning or RAG?
Understanding the tradeoffs between RAG and Fine-tuning, and owning the model vs. using a third-party host.
LLM and Fine-tuning
Implementing DoRA (an Improved LoRA) from Scratch
A powerful LoRA-variant explained in a beginner-friendly way and implemented in PyTorch.
LLM and Fine-tuning
Understanding LoRA-derived Techniques for Optimal LLM Fine-tuning
LoRA-variants explained in a beginner-friendly way.
LLM and Fine-tuning
Implementing LoRA From Scratch for Fine-tuning LLMs
Understanding the challenges of traditional fine-tuning and addressing them with LoRA.
